4. Execution model¶
A Python program is constructed from code blocks. A block is a piece of Python program text that is executed as a unit. The following are blocks: a module, a function body, and a class definition. Each command typed interactively is a block. A script file (a file given as standard input to the interpreter or specified as a command line argument to the interpreter) is a code block. A script command (a command specified on the interpreter command line with the -c option) is a code block. A module run as a top level script (as module __main__ ) from the command line using a -m argument is also a code block. The string argument passed to the built-in functions eval() and exec() is a code block.
A code block is executed in an execution frame. A frame contains some administrative information (used for debugging) and determines where and how execution continues after the code block’s execution has completed.
4.2. Naming and binding¶
4.2.1. Binding of names¶
Names refer to objects. Names are introduced by name binding operations.
The following constructs bind names:
- formal parameters to functions,
- class definitions,
- function definitions,
- assignment expressions,
- targets that are identifiers if occurring in an assignment:
- for loop header,
- after as in a with statement, except clause, except* clause, or in the as-pattern in structural pattern matching,
- in a capture pattern in structural pattern matching
The import statement of the form from . import * binds all names defined in the imported module, except those beginning with an underscore. This form may only be used at the module level.
A target occurring in a del statement is also considered bound for this purpose (though the actual semantics are to unbind the name).
Each assignment or import statement occurs within a block defined by a class or function definition or at the module level (the top-level code block).
If a name is bound in a block, it is a local variable of that block, unless declared as nonlocal or global . If a name is bound at the module level, it is a global variable. (The variables of the module code block are local and global.) If a variable is used in a code block but not defined there, it is a free variable.
Each occurrence of a name in the program text refers to the binding of that name established by the following name resolution rules.
4.2.2. Resolution of names¶
A scope defines the visibility of a name within a block. If a local variable is defined in a block, its scope includes that block. If the definition occurs in a function block, the scope extends to any blocks contained within the defining one, unless a contained block introduces a different binding for the name.
When a name is used in a code block, it is resolved using the nearest enclosing scope. The set of all such scopes visible to a code block is called the block’s environment.
When a name is not found at all, a NameError exception is raised. If the current scope is a function scope, and the name refers to a local variable that has not yet been bound to a value at the point where the name is used, an UnboundLocalError exception is raised. UnboundLocalError is a subclass of NameError .
If a name binding operation occurs anywhere within a code block, all uses of the name within the block are treated as references to the current block. This can lead to errors when a name is used within a block before it is bound. This rule is subtle. Python lacks declarations and allows name binding operations to occur anywhere within a code block. The local variables of a code block can be determined by scanning the entire text of the block for name binding operations. See the FAQ entry on UnboundLocalError for examples.
If the global statement occurs within a block, all uses of the names specified in the statement refer to the bindings of those names in the top-level namespace. Names are resolved in the top-level namespace by searching the global namespace, i.e. the namespace of the module containing the code block, and the builtins namespace, the namespace of the module builtins . The global namespace is searched first. If the names are not found there, the builtins namespace is searched. The global statement must precede all uses of the listed names.
The global statement has the same scope as a name binding operation in the same block. If the nearest enclosing scope for a free variable contains a global statement, the free variable is treated as a global.
The nonlocal statement causes corresponding names to refer to previously bound variables in the nearest enclosing function scope. SyntaxError is raised at compile time if the given name does not exist in any enclosing function scope.
The namespace for a module is automatically created the first time a module is imported. The main module for a script is always called __main__ .
Class definition blocks and arguments to exec() and eval() are special in the context of name resolution. A class definition is an executable statement that may use and define names. These references follow the normal rules for name resolution with an exception that unbound local variables are looked up in the global namespace. The namespace of the class definition becomes the attribute dictionary of the class. The scope of names defined in a class block is limited to the class block; it does not extend to the code blocks of methods – this includes comprehensions and generator expressions since they are implemented using a function scope. This means that the following will fail:
class A: a = 42 b = list(a + i for i in range(10))
4.2.3. Builtins and restricted execution¶
CPython implementation detail: Users should not touch __builtins__ ; it is strictly an implementation detail. Users wanting to override values in the builtins namespace should import the builtins module and modify its attributes appropriately.
The builtins namespace associated with the execution of a code block is actually found by looking up the name __builtins__ in its global namespace; this should be a dictionary or a module (in the latter case the module’s dictionary is used). By default, when in the __main__ module, __builtins__ is the built-in module builtins ; when in any other module, __builtins__ is an alias for the dictionary of the builtins module itself.
4.2.4. Interaction with dynamic features¶
Name resolution of free variables occurs at runtime, not at compile time. This means that the following code will print 42:
i = 10 def f(): print(i) i = 42 f()
The eval() and exec() functions do not have access to the full environment for resolving names. Names may be resolved in the local and global namespaces of the caller. Free variables are not resolved in the nearest enclosing namespace, but in the global namespace. 1 The exec() and eval() functions have optional arguments to override the global and local namespace. If only one namespace is specified, it is used for both.
4.3. Exceptions¶
Exceptions are a means of breaking out of the normal flow of control of a code block in order to handle errors or other exceptional conditions. An exception is raised at the point where the error is detected; it may be handled by the surrounding code block or by any code block that directly or indirectly invoked the code block where the error occurred.
The Python interpreter raises an exception when it detects a run-time error (such as division by zero). A Python program can also explicitly raise an exception with the raise statement. Exception handlers are specified with the try … except statement. The finally clause of such a statement can be used to specify cleanup code which does not handle the exception, but is executed whether an exception occurred or not in the preceding code.
Python uses the “termination” model of error handling: an exception handler can find out what happened and continue execution at an outer level, but it cannot repair the cause of the error and retry the failing operation (except by re-entering the offending piece of code from the top).
When an exception is not handled at all, the interpreter terminates execution of the program, or returns to its interactive main loop. In either case, it prints a stack traceback, except when the exception is SystemExit .
Exceptions are identified by class instances. The except clause is selected depending on the class of the instance: it must reference the class of the instance or a non-virtual base class thereof. The instance can be received by the handler and can carry additional information about the exceptional condition.
Exception messages are not part of the Python API. Their contents may change from one version of Python to the next without warning and should not be relied on by code which will run under multiple versions of the interpreter.
See also the description of the try statement in section The try statement and raise statement in section The raise statement .
This limitation occurs because the code that is executed by these operations is not available at the time the module is compiled.
2.1. Теория¶
Язык Python является одним из самых простых в изучении и самых приятных в использовании из языков программирования, получивших широкое распространение. Программный код на языке Python легко читать и писать, и, будучи лаконичным, он не выглядит загадочным. Python — очень выразительный язык, позволяющий уместить приложение в меньшее количество строк, чем на это потребовалось бы в других языках, таких как C++ или Java.
2.1.1. История создания¶
Разработка языка Python была начата в конце 1980-х годов сотрудником голландского института CWI (Центр математики и информатики, голл. Centrum Wiskunde & Informatica) Гвидо ван Россумом (англ. Guido van Rossum), на основе языка ABC (Рисунок 2.1.1). В феврале 1991 года Гвидо опубликовал исходный текст в группе новостей alt.sources.
Рисунок 2.1.1 — Гвидо ван Россум на конференции в 2006 г. ¶
О создании Python Гвидо ван Россум написал в 1996 г.:
«Около 6 лет назад, в декабре 1989 г., я думал над проектом в области программирования в качестве хобби, которое бы заняло меня на время Рождественских выходных. Мой офис… был закрыл, но компьютер был и дома, и, в общем, это все, что у меня было на руках. Я решил написать интерпретатор для нового скриптового языка, о котором думал в последнее время: наследника ABC, который бы оказался привлекательным для Unix/C хакеров. Пилотное название «Питон» было выбрано с одной стороны в связи с немного скептическим отношением к перспективам проекта, а с другой — из-за того, что я большой фанат шоу «Летающий цирк Монти Пайтона».
Покинув в декабре 2012 года корпорацию Google, с 2013 года Гвидо работал в компании Dropbox Inc, выйдя на пенсию в 2019, а с 2020 работает в компании Microsoft. Имея статус «великодушного пожизненного диктатора» проекта — он продолжает наблюдать за процессом разработки Python, принимая окончательные решения, когда это необходимо (не менее 50% рабочего времени по договоренности с DropBox).
Появившись сравнительно поздно, Python создавался под влиянием множества языков программирования. Так, например, влияние оказали такие языки, как:
- ABC: отступы для группировки операторов, высокоуровневые структуры данных;
- Modula-3: пакеты, модули;
- С, C++: некоторые синтаксические конструкции;
- Smalltalk: ООП;
- Java: обработка исключений и др.
Большая часть других особенностей Python (например, байт-компиляция исходного кода) также была реализована ранее в других языках.
Развитие языка происходит согласно четко регламентированному процессу создания, обсуждения, отбора и реализации документов PEP (Python Enhancement Proposal) — предложений по развитию Python.
В 2008 году, после длительного тестирования, вышла первая версия Python 3000 (или Python 3.0, также используется сокращение Py3k). В Python 3000 устранены многие недостатки архитектуры с максимально возможным (но не полным) сохранением совместимости со старыми версиями Python. На сегодня поддерживаются обе ветви развития (Python 3.x и 2.x) (сравнение и рекомендации), однако получать новый функционал будет только версия 3 6.
Ключевые вехи развития языка приведены в Таблице 2.1.1.
Таблица 2.1.1 — Основные вехи развития языка Python ¶
Актуальная версия (дата выхода) (могла устареть)
