- Lee On Coding
- How does python find packages?
- sys.path
- How sys.path gets populated
- You can manipulate sys.path
- The module __file__ attribute
- The imp module
- Ubuntu Python
- Ubuntu Python ( /usr/bin/python ):
- Python compiled from source ( /usr/local/bin/python )
- How did Ubuntu manipulate the sys.path ?
- Find python modules linux
- Windows Environment
- Где хранятся модули в Python?
- Команда import в Python
- Команда from . import
- Команда from . import *
- Так где хранятся модули в Python?
- Получаем список всех модулей Python
- Создаём свой модуль в Python
- Функция dir() в Python
- Пакеты модулей в Python
- 6. ModulesВ¶
- 6.1. More on ModulesВ¶
- 6.1.1. Executing modules as scriptsВ¶
- 6.1.2. The Module Search PathВ¶
- 6.1.3. “Compiled” Python files¶
- 6.2. Standard ModulesВ¶
- 6.3. The dir() FunctionВ¶
- 6.4. PackagesВ¶
- 6.4.1. Importing * From a PackageВ¶
- 6.4.2. Intra-package ReferencesВ¶
- 6.4.3. Packages in Multiple DirectoriesВ¶
Lee On Coding
My blog about coding and stuff.
How does python find packages?
I just ran into a situation where I compiled and installed Python 2.7.9 from source on Ubuntu, but Python could not find the packages I had previously installed. This naturally raises the question — how does Python know where to find packages when you call import ? This post applies specifically to Python 2.7.9, but I’m guessing Python 3x works very similarly.
In this post I first describe how Python finds packages, and then I’ll finish with the discovery I made regarding the default Python that ships with Ubuntu and how it differs from vanilla Python in how it finds packages.
sys.path
Python imports work by searching the directories listed in sys.path .
Using my default Ubuntu 14.04 Python:
So Python will find any packages that have been installed to those locations.
How sys.path gets populated
As the docs explain, sys.path is populated using the current working directory, followed by directories listed in your PYTHONPATH environment variable, followed by installation-dependent default paths, which are controlled by the site module.
You can read more about sys.path in the Python docs.
Assuming your PYTHONPATH environment variable is not set, sys.path will consist of the current working directory plus any manipulations made to it by the site module.
The site module is automatically imported when you start Python, you can read more about how it manipulates your sys.path in the Python docs.
It’s a bit involved.
You can manipulate sys.path
You can manipulate sys.path during a Python session and this will change how Python finds modules. For example:
The module __file__ attribute
When you import a module, you usually can check the __file__ attribute of the module to see where the module is in your filesystem:
However, the Python docs state that:
The file attribute is not present for C modules that are statically linked into the interpreter; for extension modules loaded dynamically from a shared library, it is the pathname of the shared library file.
So, for example this doesn’t work:
It makes sense that the sys module is statically linked to the interpreter — it is essentially part of the interpreter!
The imp module
Python exposes the entire import system through the imp module. That’s pretty cool that all of this stuff is exposed for us to abuse, if we wanted to.
imp.find_module can be used to find a module:
You can also import and arbitrary Python source as a module using imp.load_source . This is the same example before, except imports our module using imp instead of by manipulating sys.path :
Passing ‘hi’ to imp.load_source simply sets the __name__ attribute of the module.
Ubuntu Python
Now back to the issue of missing packages after installing a new version of Python compiled from source. By comparing the sys.path from both the Ubuntu Python, which resides at /usr/bin/python , and the newly installed Python, which resides at /usr/local/bin/python , I could sort things out:
Ubuntu Python ( /usr/bin/python ):
Python compiled from source ( /usr/local/bin/python )
Turns out what mattered for me was dist-packages vs. site-packages . Using Ubuntu’s Python, my packages were installed to /usr/local/lib/python2.7/dist-packages , whereas the new Python I installed expects packages to be installed to /usr/local/lib/python2.7/site-packages . I just had to manipulate the PYTHONPATH environment variable to point to dist-packages in order to gain access to the previously installed packaged with the newly installed version of Python.
How did Ubuntu manipulate the sys.path ?
So how does the Ubuntu distribution of Python know to use /usr/local/lib/python2.7/dist-packages in sys.path ? It’s hardcoded into their site module! First, find where the site module code lives:
Here is an excerpt from Ubuntu Python’s site.py , which I peeked by opening /usr/lib/python2.7/site.py in a text editor. First, a comment at the top:
For Debian and derivatives, this sys.path is augmented with directories for packages distributed within the distribution. Local addons go into /usr/local/lib/python /dist-packages, Debian addons install into /usr/
/python /dist-packages. /usr/lib/python /site-packages is not used.
OK so there you have it. They explain how the Debian distribution of Python is different.
And now, for the code that implementes this change:
It’s all there, if you are crazy enough to dig this deep.
© Lee Mendelowitz – Built with Pure Theme for Pelican
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Find python modules linux
For modules to be available for use, the Python interpreter must be able to locate the module file. Python has a set of directories in which it looks for module files. This set of directories is called the search path, and is analogous to the PATH environment variable used by an operating system to locate an executable file.
Python’s search path is built from a number of sources:
PYTHONHOME is used to define directories that are part of the Python installation. If this environment variable is not defined, then a standard directory structure is used. For Windows, the standard location is based on the directory into which Python is installed. For most Linux environments, Python is installed under /usr/local , and the libraries can be found there. For Mac OS, the home directory is under /Library/Frameworks/Python.framework .
PYTHONPATH is used to add directories to the path. This environment variable is formatted like the OS PATH variable, with a series of filenames separated by : ‘s (or ; ‘s for Windows).
Script Directory. If you run a Python script, that script’s directory is placed first on the search path so that locally-defined moules will be used instead of built-in modules of the same name.
The site module’s locations are also added. (This can be disabled by starting Python with the -S option.) The site module will use the PYTHONHOME location(s) to create up to four additional directories. Generally, the most interesting one is the site-packages directory. This directory is a handy place to put additional modules you’ve downloaded. Additionally, this directory can contain .PTH files. The site module reads .PTH files and puts the named directories onto the search path.
The search path is defined by the path variable in the sys module. If we import sys , we can display sys.path . This is very handy for debugging. When debugging shell scripts, it can help to run ‘ python -c ‘import sys; print sys.path’ just to see parts of the Python environment settings.
Installing a module, then, is a matter of assuring that the module appears on the search path. There are four central methods for doing this.
Some packages will suggest you create a directory and place the package in that directory. This may be done by downloading and unzipping a file. It may be done by using Subversion and sychronizing your subversion copy with the copy on a server. Either way, you will likely only need to create an operating system link to this directory and place that link in site-packages directory.
Some packages will suggest you download (or use subversion) to create a temporary copy. They will provide you with a script — typically based on setup.py — which moves files into the correct locations. This is called the distutils distribution. This will generally copy the module files to the site-packages directory.
Some packages will rely on setuptools . This is a package from the Python Enterprise Application Kit that extends distuils to further automates download and installation. This tool, also, works by moving the working library modules to the site-packages directory.
Extending the search path. Either set the PYTHONPATH environment variable, or put .PTH files in the site-packages directory.
Windows Environment
In the Windows environment, the Python_Path symbol in the Windows registry is used to locate modules.
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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.
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6. ModulesВ¶
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 enter the names of the functions defined in fibo directly in the current symbol table; it only enters 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 ModulesВ¶
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 symbol table, which is used as the global symbol table 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 are placed in the importing module’s global symbol table.
There is a variant of the import statement that imports names from a module directly into the importing module’s symbol table. For example:
This does not introduce the module name from which the imports are taken in the local symbol table (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 scriptsВ¶
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 PathВ¶
When a module named spam is imported, the interpreter first searches for a built-in module with that name. 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 ModulesВ¶
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() FunctionВ¶
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. PackagesВ¶
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 PackageВ¶
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 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 ReferencesВ¶
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 DirectoriesВ¶
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 вЂstatements’ that are вЂexecuted’; the execution of a module-level function definition enters the function name in the module’s global symbol table.
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