Hướng dẫn dùng example glossary python
>>> The default Python prompt of the interactive shell. Often seen for code examples which can be executed interactively in the interpreter. ... Can refer to:
A tool that tries to convert Python 2.x code to Python 3.x code by handling most of the incompatibilities which can be detected by parsing the source and traversing the parse tree. 2to3 is available in the standard library
as Abstract base classes complement
duck-typing by providing a way to define interfaces when other techniques like 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 are stored in the See variable annotation, function annotation, PEP 484 and PEP 526, which describe this functionality. Also see Annotations Best Practices for best practices on working with annotations. argumentA value passed to a function (or method) when calling the function. There are two kinds of argument:
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 managerAn object which controls the environment seen in an A function which returns an asynchronous generator iterator. It looks like a coroutine function defined with 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 An object created by a asynchronous generator function. This is an asynchronous iterator which when called using the Each An object, that can be used in an An object that implements the 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
Identifiers and keywords, for example using An object that can be used in an Benevolent Dictator For Life, a.k.a. Guido van Rossum, Python’s creator. binary fileA file object able to read and write
bytes-like objects. Examples of binary files are files opened in binary mode ( See
also text file for a file object able to read and write In Python’s C API, a borrowed reference is a reference to an object. It does not modify the object reference count. 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 An object that supports the Buffer Protocol and can export a C-contiguous buffer. This includes all
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 Python source code is compiled into bytecode, the internal representation of a Python program in the CPython interpreter. The bytecode is also cached in A list of bytecode instructions can be found in the documentation for the dis module. callbackA subroutine function which is passed as an argument to be executed at some point in the future. classA template for creating user-defined objects. Class definitions normally contain method definitions which operate on instances of the class. class variableA variable defined in a class and intended to be modified only at class level (i.e., not in an instance of the class). coercionThe implicit conversion of an instance of one type to another during an operation which involves two arguments of the same type. For example, 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 An object which controls the environment seen in a A variable which can have different values
depending on its context. This is similar to Thread-Local Storage in which each execution thread may have a different value for a variable. However, with context variables, there may be several contexts in one execution thread and the main usage for context variables is to keep track of variables in concurrent asynchronous tasks. See 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. coroutineCoroutines 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 A function which returns a coroutine object. A coroutine function may be defined with the 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. decoratorA function returning another function, usually applied as a function transformation using the 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. descriptorAny object which defines the methods For more information about descriptors’ methods, see Implementing Descriptors or the Descriptor How To Guide. dictionaryAn associative array, where arbitrary keys are mapped to values. The keys can be any object with A compact way to process all or part of the elements in an iterable and return a dictionary with the results. The objects returned from 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 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 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 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 statements which cannot be used as expressions, such as A module written in C or C++, using Python’s C API to interact with the core and with user code. f-stringString literals prefixed with An object exposing a
file-oriented API (with methods such as There are actually three categories of file objects: raw
binary files, buffered binary files and text files. Their interfaces are defined in the
A synonym for file object. filesystem encoding and error handlerEncoding 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
The The filesystem encoding and error handler are configured at Python startup by the See also the locale encoding. finderAn object that tries to find the loader for a module that is being imported. Since Python 3.3, there are two types of finder: meta path finders for use with See PEP 302, PEP 420 and PEP 451 for much more detail. floor divisionMathematical division that rounds down to nearest integer. The floor division operator is 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 annotationAn 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 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, >>> 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
A function which returns a generator iterator. It looks like a normal function except that it contains
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 iteratorAn object created by a generator function. Each An expression that returns an iterator. It looks like a normal expression followed by a >>> sum(i*i for i in range(10)) # sum of squares 0, 1, 4, ... 81 285generic 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
A type that can be parameterized; typically a
container class such as For more details, see generic alias types, PEP 483, PEP
484, PEP 585, and the See global interpreter lock. global interpreter lockThe 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 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. Past efforts to create a “free-threaded” interpreter (one which locks shared data at a much finer granularity) have not been successful because performance suffered in the common single-processor case. It is believed that overcoming this performance issue would make the implementation much more complicated and therefore costlier to maintain. hash-based pycA 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. hashableAn object is hashable if it has a hash value which never changes during its lifetime (it needs a 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 An Integrated Development and Learning Environment for Python. IDLE is a basic editor and interpreter environment which ships with the standard distribution of Python. immutableAn 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. import pathA 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 The process by which Python code in one module is made available to Python code in another module. importerAn object that both finds and loads a module; both a finder and loader object. interactivePython 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 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 shutdownWhen 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 An object capable of returning its members one at a time. Examples of iterables include all sequence types (such as Iterables can be used in a An object representing a stream of data. Repeated calls to the iterator’s More information can be found in Iterator Types. CPython implementation detail: CPython does not consistently apply the requirement that an iterator define A key function or collation function is a callable that returns a value used
for sorting or ordering. For example, A number of tools in Python accept key functions to control how elements are ordered or grouped. They include There are several ways to create a key function. For example. the
See argument. lambdaAn anonymous inline function consisting of a single expression which is evaluated when the function is called. The syntax to create a lambda function is 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 In a multi-threaded environment, the LBYL approach can risk introducing a race condition between “the looking” and “the leaping”. For
example, the code, On Unix, it is the encoding of the LC_CTYPE locale. It can be set with On Windows, it is the ANSI code page (ex:
Python uses the filesystem encoding and error handler to convert between Unicode filenames and bytes filenames. listA 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 comprehensionA compact way to process all or part of the elements in a sequence and return a list with the results. An object that loads a module. It must define a method named An informal synonym for special method. mappingA container object that supports arbitrary key lookups and implements the methods specified in the
A finder returned by a search of See 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. methodA 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
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. moduleAn 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 specA namespace containing the import-related information used to load a module. An instance of
See method resolution order. mutableMutable objects can change their value but keep their
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 >>> 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 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
A PEP 420 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 See also module. nested scopeThe 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 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 Any data with state (attributes or value) and defined behavior (methods). Also the ultimate base class of any new-style class. packageA Python module which can contain submodules or recursively, subpackages. Technically, a package is a Python module with an See also regular package and namespace package. parameterA 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:
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 A single location on the import path which the path based finder consults to find modules for importing. path entry finderA finder returned by a callable on
See
A callable on the One of the default meta path finders which searches an import path for modules. path-like objectAn object representing a file system path. A path-like object is either a 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. portionA 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 argumentSee argument. provisional APIA 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 gratuitously – they will occur only if serious fundamental flaws are uncovered that were missed prior to the inclusion of the API. Even for provisional APIs, backwards incompatible changes are seen as a “solution of last resort” - every attempt will still be made to find a backwards compatible resolution to any identified problems. This process allows the standard library to continue to evolve over time, without locking in problematic design errors for extended periods of time. See PEP 411 for more details. provisional packageSee provisional API. Python 3000Nickname for the Python 3.x release line (coined long ago when the release of version 3 was something in the distant future.) This is also abbreviated “Py3k”. PythonicAn idea or piece of code which closely follows the most common idioms of the Python language, rather than implementing code using concepts common to other languages. For example, a common idiom in Python is to loop over all elements of an iterable using a
for i in range(len(food)): print(food[i]) As opposed to the cleaner, Pythonic method: for piece in food: print(piece)qualified name A dotted name showing the “path” from a module’s global scope to a class, function or method defined in that module, as defined in PEP 3155. For top-level functions and classes, the qualified name is the same as the object’s name: >>> class C: ... class D: ... def meth(self): ... pass ... >>> C.__qualname__ 'C' >>> C.D.__qualname__ 'C.D' >>> C.D.meth.__qualname__ 'C.D.meth' When used to refer to modules, the fully qualified name means the entire dotted path to the module, including any parent packages, e.g. >>> import email.mime.text >>> email.mime.text.__name__ 'email.mime.text'reference count The
number of references to an object. When the reference count of an object drops to zero, it is deallocated. Reference counting is generally not visible to Python code, but it is a key element of the CPython implementation. The A traditional package, such as a directory containing an See also namespace package. __slots__A declaration inside a class that saves memory by pre-declaring space for instance attributes and eliminating instance dictionaries. Though popular, the technique is somewhat tricky to get right and is best reserved for rare cases where there are large numbers of instances in a memory-critical application. sequenceAn iterable which supports efficient element access using integer indices via the The A compact way to process all or part of the elements in an iterable and return a set with the results. A form of generic function dispatch where the implementation is chosen based on the type of a single argument. sliceAn object usually
containing a portion of a sequence. A slice is created using the subscript notation, A method that is called implicitly by Python to execute a certain operation on a type, such as addition. Such methods have names starting and ending with double underscores. Special methods are documented in Special method names. statementA statement is part of a suite (a “block” of code). A statement is either an expression or one of several constructs with a keyword, such as In Python’s C API, a strong reference is a reference to an object which increments the object’s reference count when it is created and decrements the object’s reference count when it is deleted. The See also borrowed reference. text encodingA string in Python is a sequence of Unicode code
points (in range Serializing a string into a sequence of bytes is known as “encoding”, and recreating the string from the sequence of bytes is known as “decoding”. There are a variety of different text serialization codecs, which are collectively referred to as “text encodings”. text fileA file object able to read and write See also binary file for a file object able to read and write bytes-like objects. triple-quoted stringA string which is bound by three instances of either a quotation mark (”) or an apostrophe (‘). While they don’t provide any functionality not available with single-quoted strings, they are useful for a number of reasons. They allow you to include unescaped single and double quotes within a string and they can span multiple lines without the use of the continuation character, making them especially useful when writing docstrings. typeThe type of a Python object determines what kind of object it is; every object has a type. An object’s type is accessible as its
A synonym for a type, created by assigning the type to an identifier. Type aliases are useful for simplifying type hints. For example: def remove_gray_shades( colors: list[tuple[int, int, int]]) -> list[tuple[int, int, int]]: pass could be made more readable like this: Color = tuple[int, int, int] def remove_gray_shades(colors: list[Color]) -> list[Color]: pass See An annotation that specifies the expected type for a variable, a class attribute, or a function parameter or return value. Type hints are optional and are not enforced by Python but they are useful to static type analysis tools, and aid IDEs with code completion and refactoring. Type hints of global variables, class attributes, and functions, but not local variables, can be accessed using
See A manner of interpreting text streams in which all of the following are recognized as ending a line: the Unix end-of-line convention An annotation of a variable or a class attribute. When annotating a variable or a class attribute, assignment is optional: class C: field: 'annotation' Variable annotations are usually used for type hints: for example this variable is expected to take Variable annotation syntax is explained in section Annotated assignment statements. See function annotation, PEP 484 and PEP 526, which describe this functionality. Also see Annotations Best Practices for best practices on working with annotations. virtual environmentA cooperatively isolated runtime environment that allows Python users and applications to install and upgrade Python distribution packages without interfering with the behaviour of other Python applications running on the same system. See also A computer defined entirely in software. Python’s virtual machine executes the bytecode emitted by the bytecode compiler. Zen of PythonListing of Python design principles and philosophies that are helpful in understanding and using the language. The listing can be found by typing “ |