Где хранятся библиотеки python
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Где хранятся библиотеки python

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Where does Python look for modules?¶

Let’s say we have written a Python module and saved it as a_module.py , in a directory called code .

We also have a script called a_script.py in a directory called scripts .

We want to be able to import the code in a_module.py to use in a_script.py . So, we want to be able to put his line in a_script.py :

The module and script might look like this:

At the moment, a_script.py will fail with:

When Python hits the line import a_module , it tries to find a package or a module called a_module . A package is a directory containing modules, but we will only consider modules for now. A module is a file with a matching extension, such as .py . So, Python is looking for a file a_module.py , and not finding it.

You will see the same effect at the interactive Python console, or in IPython:

Python looks for modules in “sys.path”¶

Python has a simple algorithm for finding a module with a given name, such as a_module . It looks for a file called a_module.py in the directories listed in the variable sys.path .

The a_module.py file is in the code directory, and this directory is not in the sys.path list.

Because sys.path is just a Python list, like any other, we can make the import work by appending the code directory to the list.

There are various ways of making sure a directory is always on the Python sys.path list when you run Python, including:

  • put the directory into the contents of the PYTHONPATH environment variable – Using PYTHONPATH
  • make the module part of an installable package, and install it – see: making a Python package.

As a crude hack, you can also put your code directory on the Python sys.path at the top of the files that need it:

The simple append above will only work when running the script from a directory containing the code subdirectory. For example:

This is because the directory code that we specified is a relative path, and therefore Python looks for the code directory in the current working directory.

To make the hack work when running the code from any directory, you could use some path manipulation on the The “__file__” variable :

6. Modules¶

If you quit from the Python interpreter and enter it again, the definitions you have made (functions and variables) are lost. Therefore, if you want to write a somewhat longer program, you are better off using a text editor to prepare the input for the interpreter and running it with that file as input instead. This is known as creating a script. As your program gets longer, you may want to split it into several files for easier maintenance. You may also want to use a handy function that you’ve written in several programs without copying its definition into each program.

To support this, Python has a way to put definitions in a file and use them in a script or in an interactive instance of the interpreter. Such a file is called a module; definitions from a module can be imported into other modules or into the main module (the collection of variables that you have access to in a script executed at the top level and in calculator mode).

A module is a file containing Python definitions and statements. The file name is the module name with the suffix .py appended. Within a module, the module’s name (as a string) is available as the value of the global variable __name__ . For instance, use your favorite text editor to create a file called fibo.py in the current directory with the following contents:

Now enter the Python interpreter and import this module with the following command:

This does not add the names of the functions defined in fibo directly to the current namespace (see Python Scopes and Namespaces for more details); it only adds the module name fibo there. Using the module name you can access the functions:

If you intend to use a function often you can assign it to a local name:

6.1. More on Modules¶

A module can contain executable statements as well as function definitions. These statements are intended to initialize the module. They are executed only the first time the module name is encountered in an import statement. 1 (They are also run if the file is executed as a script.)

Each module has its own private namespace, which is used as the global namespace by all functions defined in the module. Thus, the author of a module can use global variables in the module without worrying about accidental clashes with a user’s global variables. On the other hand, if you know what you are doing you can touch a module’s global variables with the same notation used to refer to its functions, modname.itemname .

Modules can import other modules. It is customary but not required to place all import statements at the beginning of a module (or script, for that matter). The imported module names, if placed at the top level of a module (outside any functions or classes), are added to the module’s global namespace.

There is a variant of the import statement that imports names from a module directly into the importing module’s namespace. For example:

This does not introduce the module name from which the imports are taken in the local namespace (so in the example, fibo is not defined).

There is even a variant to import all names that a module defines:

This imports all names except those beginning with an underscore ( _ ). In most cases Python programmers do not use this facility since it introduces an unknown set of names into the interpreter, possibly hiding some things you have already defined.

Note that in general the practice of importing * from a module or package is frowned upon, since it often causes poorly readable code. However, it is okay to use it to save typing in interactive sessions.

If the module name is followed by as , then the name following as is bound directly to the imported module.

This is effectively importing the module in the same way that import fibo will do, with the only difference of it being available as fib .

It can also be used when utilising from with similar effects:

For efficiency reasons, each module is only imported once per interpreter session. Therefore, if you change your modules, you must restart the interpreter – or, if it’s just one module you want to test interactively, use importlib.reload() , e.g. import importlib; importlib.reload(modulename) .

6.1.1. Executing modules as scripts¶

When you run a Python module with

the code in the module will be executed, just as if you imported it, but with the __name__ set to "__main__" . That means that by adding this code at the end of your module:

you can make the file usable as a script as well as an importable module, because the code that parses the command line only runs if the module is executed as the “main” file:

If the module is imported, the code is not run:

This is often used either to provide a convenient user interface to a module, or for testing purposes (running the module as a script executes a test suite).

6.1.2. The Module Search Path¶

When a module named spam is imported, the interpreter first searches for a built-in module with that name. These module names are listed in sys.builtin_module_names . If not found, it then searches for a file named spam.py in a list of directories given by the variable sys.path . sys.path is initialized from these locations:

The directory containing the input script (or the current directory when no file is specified).

PYTHONPATH (a list of directory names, with the same syntax as the shell variable PATH ).

The installation-dependent default (by convention including a site-packages directory, handled by the site module).

On file systems which support symlinks, the directory containing the input script is calculated after the symlink is followed. In other words the directory containing the symlink is not added to the module search path.

After initialization, Python programs can modify sys.path . The directory containing the script being run is placed at the beginning of the search path, ahead of the standard library path. This means that scripts in that directory will be loaded instead of modules of the same name in the library directory. This is an error unless the replacement is intended. See section Standard Modules for more information.

6.1.3. “Compiled” Python files¶

To speed up loading modules, Python caches the compiled version of each module in the __pycache__ directory under the name module. version .pyc , where the version encodes the format of the compiled file; it generally contains the Python version number. For example, in CPython release 3.3 the compiled version of spam.py would be cached as __pycache__/spam.cpython-33.pyc . This naming convention allows compiled modules from different releases and different versions of Python to coexist.

Python checks the modification date of the source against the compiled version to see if it’s out of date and needs to be recompiled. This is a completely automatic process. Also, the compiled modules are platform-independent, so the same library can be shared among systems with different architectures.

Python does not check the cache in two circumstances. First, it always recompiles and does not store the result for the module that’s loaded directly from the command line. Second, it does not check the cache if there is no source module. To support a non-source (compiled only) distribution, the compiled module must be in the source directory, and there must not be a source module.

Some tips for experts:

You can use the -O or -OO switches on the Python command to reduce the size of a compiled module. The -O switch removes assert statements, the -OO switch removes both assert statements and __doc__ strings. Since some programs may rely on having these available, you should only use this option if you know what you’re doing. “Optimized” modules have an opt- tag and are usually smaller. Future releases may change the effects of optimization.

A program doesn’t run any faster when it is read from a .pyc file than when it is read from a .py file; the only thing that’s faster about .pyc files is the speed with which they are loaded.

The module compileall can create .pyc files for all modules in a directory.

There is more detail on this process, including a flow chart of the decisions, in PEP 3147.

6.2. Standard Modules¶

Python comes with a library of standard modules, described in a separate document, the Python Library Reference (“Library Reference” hereafter). Some modules are built into the interpreter; these provide access to operations that are not part of the core of the language but are nevertheless built in, either for efficiency or to provide access to operating system primitives such as system calls. The set of such modules is a configuration option which also depends on the underlying platform. For example, the winreg module is only provided on Windows systems. One particular module deserves some attention: sys , which is built into every Python interpreter. The variables sys.ps1 and sys.ps2 define the strings used as primary and secondary prompts:

These two variables are only defined if the interpreter is in interactive mode.

The variable sys.path is a list of strings that determines the interpreter’s search path for modules. It is initialized to a default path taken from the environment variable PYTHONPATH , or from a built-in default if PYTHONPATH is not set. You can modify it using standard list operations:

6.3. The dir() Function¶

The built-in function dir() is used to find out which names a module defines. It returns a sorted list of strings:

Without arguments, dir() lists the names you have defined currently:

Note that it lists all types of names: variables, modules, functions, etc.

dir() does not list the names of built-in functions and variables. If you want a list of those, they are defined in the standard module builtins :

6.4. Packages¶

Packages are a way of structuring Python’s module namespace by using “dotted module names”. For example, the module name A.B designates a submodule named B in a package named A . Just like the use of modules saves the authors of different modules from having to worry about each other’s global variable names, the use of dotted module names saves the authors of multi-module packages like NumPy or Pillow from having to worry about each other’s module names.

Suppose you want to design a collection of modules (a “package”) for the uniform handling of sound files and sound data. There are many different sound file formats (usually recognized by their extension, for example: .wav , .aiff , .au ), so you may need to create and maintain a growing collection of modules for the conversion between the various file formats. There are also many different operations you might want to perform on sound data (such as mixing, adding echo, applying an equalizer function, creating an artificial stereo effect), so in addition you will be writing a never-ending stream of modules to perform these operations. Here’s a possible structure for your package (expressed in terms of a hierarchical filesystem):

When importing the package, Python searches through the directories on sys.path looking for the package subdirectory.

The __init__.py files are required to make Python treat directories containing the file as packages. This prevents directories with a common name, such as string , unintentionally hiding valid modules that occur later on the module search path. In the simplest case, __init__.py can just be an empty file, but it can also execute initialization code for the package or set the __all__ variable, described later.

Users of the package can import individual modules from the package, for example:

This loads the submodule sound.effects.echo . It must be referenced with its full name.

An alternative way of importing the submodule is:

This also loads the submodule echo , and makes it available without its package prefix, so it can be used as follows:

Yet another variation is to import the desired function or variable directly:

Again, this loads the submodule echo , but this makes its function echofilter() directly available:

Note that when using from package import item , the item can be either a submodule (or subpackage) of the package, or some other name defined in the package, like a function, class or variable. The import statement first tests whether the item is defined in the package; if not, it assumes it is a module and attempts to load it. If it fails to find it, an ImportError exception is raised.

Contrarily, when using syntax like import item.subitem.subsubitem , each item except for the last must be a package; the last item can be a module or a package but can’t be a class or function or variable defined in the previous item.

6.4.1. Importing * From a Package¶

Now what happens when the user writes from sound.effects import * ? Ideally, one would hope that this somehow goes out to the filesystem, finds which submodules are present in the package, and imports them all. This could take a long time and importing sub-modules might have unwanted side-effects that should only happen when the sub-module is explicitly imported.

The only solution is for the package author to provide an explicit index of the package. The import statement uses the following convention: if a package’s __init__.py code defines a list named __all__ , it is taken to be the list of module names that should be imported when from package import * is encountered. It is up to the package author to keep this list up-to-date when a new version of the package is released. Package authors may also decide not to support it, if they don’t see a use for importing * from their package. For example, the file sound/effects/__init__.py could contain the following code:

This would mean that from sound.effects import * would import the three named submodules of the sound.effects package.

If __all__ is not defined, the statement from sound.effects import * does not import all submodules from the package sound.effects into the current namespace; it only ensures that the package sound.effects has been imported (possibly running any initialization code in __init__.py ) and then imports whatever names are defined in the package. This includes any names defined (and submodules explicitly loaded) by __init__.py . It also includes any submodules of the package that were explicitly loaded by previous import statements. Consider this code:

In this example, the echo and surround modules are imported in the current namespace because they are defined in the sound.effects package when the from. import statement is executed. (This also works when __all__ is defined.)

Although certain modules are designed to export only names that follow certain patterns when you use import * , it is still considered bad practice in production code.

Remember, there is nothing wrong with using from package import specific_submodule ! In fact, this is the recommended notation unless the importing module needs to use submodules with the same name from different packages.

6.4.2. Intra-package References¶

When packages are structured into subpackages (as with the sound package in the example), you can use absolute imports to refer to submodules of siblings packages. For example, if the module sound.filters.vocoder needs to use the echo module in the sound.effects package, it can use from sound.effects import echo .

You can also write relative imports, with the from module import name form of import statement. These imports use leading dots to indicate the current and parent packages involved in the relative import. From the surround module for example, you might use:

Note that relative imports are based on the name of the current module. Since the name of the main module is always "__main__" , modules intended for use as the main module of a Python application must always use absolute imports.

6.4.3. Packages in Multiple Directories¶

Packages support one more special attribute, __path__ . This is initialized to be a list containing the name of the directory holding the package’s __init__.py before the code in that file is executed. This variable can be modified; doing so affects future searches for modules and subpackages contained in the package.

While this feature is not often needed, it can be used to extend the set of modules found in a package.

In fact function definitions are also ‘statements’ that are ‘executed’; the execution of a module-level function definition adds the function name to the module’s global namespace.

Где хранятся модули в Python?


Система модулей даёт возможность логически организовать код на Python. Кроме того, группирование в модули значительно облегчает сам процесс написания кода, плюс делает его более понятным. В этой статье поговорим, что такое модуль в Python, где он хранится и как обрабатывается.

Модуль в Python — это файл, в котором содержится код на Python. Любой модуль в Python может включать в себя переменные, объявления функций и классов. Вдобавок ко всемe, в модуле может содержаться исполняемый код.

Команда import в Python

Позволяет использовать любой файл Python в качестве модуля в другом файле. Синтаксис прост:

Как только Python-интерпретатор встречает команду import, он выполняет импорт модуля, если он есть в пути поиска Python. Что касается пути поиска Python, то речь идёт о списке директорий, в которых интерпретатор выполняет поиск перед загрузкой модуля. Посмотрите на пример кода при использовании модуля math:

Помните, что модуль загружается только один раз, вне зависимости от того, какое количество раз вы его импортировали. Таким образом исключается цикличное выполнение содержимого модуля.

Команда from . import

Команда from . import даёт возможность выполнить импорт не всего модуля целиком, а лишь конкретного его содержимого:

Обратите внимание, что выражение from . import не импортирует модуль полностью, а лишь предоставляет доступ к объектам, указанным нами.

Команда from . import *

Также в Python мы можем импортировать из модуля переменные, классы и функции за один раз. Чтобы это выполнить, применяется конструкция from . import *:

Использовать данную конструкцию нужно осторожно, ведь при импорте нескольких модулей можно запутаться в собственном коде.

Так где хранятся модули в Python?

При импорте модуля, интерпретатор Python пытается найти модуль в следующих местах: 1. Директория, где находится файл, в котором вызывается команда импорта. 2. Директория, определённая в консольной переменной PYTHONPATH (если модуль не найден с первого раза). 3. Путь, заданный по умолчанию (если модуль не найден в предыдущих двух случаях).

Что касается пути поиска, то он сохраняется в переменной path в системном модуле sys. А переменная sys.path включает в себя все 3 вышеописанных места поиска.


Получаем список всех модулей Python

Чтобы получить полный список модулей, установленных на ПК, используют команду help(«modules») .


Создаём свой модуль в Python

Для создания собственного модуля в Python нужно сохранить ваш скрипт с расширением .py. После этого он станет доступным в любом другом файле. Давайте создадим 2 файла: module_1.py и module_2.py, а потом сохраним их в одной директории. В первом файле запишем:

А во втором вызовем функцию:

После выполнения кода 2-го файла получим:

Функция dir() в Python

Возвратит отсортированный список строк с содержанием всех имён, определенных в модуле.


Пакеты модулей в Python

Несколько файлов-модулей с кодом можно объединить в пакеты модулей. Пакет модулей — это директория, включающая в себя несколько отдельных файлов-скриптов.

Представьте, что у нас следующая структура:

В файле inside_file.py определена некоторая функция foo. В итоге, дабы получить доступ к этой функции, в файле my_file нужно выполнить:

Также нужно обратить внимание на то, есть ли внутри директории my_package файл init.py. Это может быть и пустой файл, сообщающий Python, что директория является пакетом модулей. В Python 3 включать файл init.py в пакет модулей уже не обязательно, но мы рекомендуем всё же делать это, чтобы обеспечить обратную совместимость.

Where are the python modules stored?

I have recently started learning Python and I have 2 questions relating to modules.

  1. Is there a way to obtain a list of Python modules available (i.e. installed) on a machine?
  2. I am using Ubuntu Karmic and Synaptic for package management. I have just installed a python module.Where is the module code actually stored on my machine? (is there a default [recommended] location that modules are stored)?

Eric Leschinski's user avatar

10 Answers 10

  1. Is there a way to obtain a list of Python modules available (i.e. installed) on a machine?

This works for me:

  1. Where is the module code actually stored on my machine?

Usually in /lib/site-packages in your Python folder. (At least, on Windows.)

You can use sys.path to find out what directories are searched for modules.

wjandrea's user avatar

On python command line, first import that module for which you need location.

For example to find out «pygal» location:

PanNik's user avatar

If you are using pip :

Sample output of pip show tensorflow :

The installed location is shown at Location:/home/user/.local/lib/python3.6/site-packages .

On Windows machine python modules are located at (system drive and python version may vary):

Bhaskar Jagadeesha's user avatar

You can find module code by first listing the modules:

This spits out a list of modules Python can import. At the bottom of this list is a phrase:

Enter any module name to get more help. Or, type «modules spam» to search for modules whose name or summary contain the string «spam».

To find module location:

A lot of information here. Scroll to the bottom to find its location

Copy link. To see code, after exiting Python REPL:

  1. You can iterate through directories listed in sys.path to find all modules (except builtin ones).
  2. It’ll probably be somewhere around /usr/lib/pythonX.X/site-packages (again, see sys.path ). And consider using native Python package management (via pip or easy_install , plus yolk ) instead, packages in Linux distros-maintained repositories tend to be outdated.

If you are using conda or pip to install modules you can use

to display all the modules. This will display all the modules in the terminal itself and is much faster than

1) Using the help function

Get into the python prompt and type the following command:

This will list all the modules installed in the system. You don’t need to install any additional packages to list them, but you need to manually search or filter the required module from the list.

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