> For the complete documentation index, see [llms.txt](https://bryan-guner.gitbook.io/my-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://bryan-guner.gitbook.io/my-docs/pythonnotes/misc/untitled/untitled-1.md).

# Python Modules & Python Packages

the difference

This article explores Python **modules** and Python **packages**, two mechanisms that facilitate **modular programming**.

**Modular programming** refers to the process of breaking a large, unwieldy programming task into separate, smaller, more manageable subtasks or **modules**. Individual modules can then be cobbled together like building blocks to create a larger application.

There are several advantages to **modularizing** code in a large application:

* **Simplicity:** Rather than focusing on the entire problem at hand, a module typically focuses on one relatively small portion of the problem. If you’re working on a single module, you’ll have a smaller problem domain to wrap your head around. This makes development easier and less error-prone.
* **Maintainability:** Modules are typically designed so that they enforce logical boundaries between different problem domains. If modules are written in a way that minimizes interdependency, there is decreased likelihood that modifications to a single module will have an impact on other parts of the program. (You may even be able to make changes to a module without having any knowledge of the application outside that module.) This makes it more viable for a team of many programmers to work collaboratively on a large application.
* **Reusability:** Functionality defined in a single module can be easily reused (through an appropriately defined interface) by other parts of the application. This eliminates the need to duplicate code.
* **Scoping:** Modules typically define a separate [**namespace**](https://realpython.com/python-namespaces-scope/), which helps avoid collisions between identifiers in different areas of a program. (One of the tenets in the [Zen of Python](https://www.python.org/dev/peps/pep-0020) is *Namespaces are one honking great idea—let’s do more of those!*)

**Functions**, **modules** and **packages** are all constructs in Python that promote code modularization.

**Free PDF Download:** [Python 3 Cheat Sheet](https://realpython.com/bonus/python-cheat-sheet-short/)

### Python Modules: Overview

There are actually three different ways to define a **module** in Python:

1. A module can be written in Python itself.
2. A module can be written in **C** and loaded dynamically at run-time, like the `re` ([**regular expression**](https://realpython.com/regex-python/)) module.
3. A **built-in** module is intrinsically contained in the interpreter, like the [`itertools` module](https://realpython.com/python-itertools/).

A module’s contents are accessed the same way in all three cases: with the `import` statement.

Here, the focus will mostly be on modules that are written in Python. The cool thing about modules written in Python is that they are exceedingly straightforward to build. All you need to do is create a file that contains legitimate Python code and then give the file a name with a `.py` extension. That’s it! No special syntax or voodoo is necessary.

For example, suppose you have created a file called `mod.py` containing the following:

***mod.py***

```
s = "If Comrade Napoleon says it, it must be right."
a = [100, 200, 300]

def foo(arg):
    print(f'arg = {arg}')

class Foo:
    pass
```

Several objects are defined in `mod.py`:

* `s` (a string)
* `a` (a list)
* `foo()` (a function)
* `Foo` (a class)

Assuming `mod.py` is in an appropriate location, which you will learn more about shortly, these objects can be accessed by **importing** the module as follows:>>>

```
>>> import mod
>>> print(mod.s)
If Comrade Napoleon says it, it must be right.
>>> mod.a
[100, 200, 300]
>>> mod.foo(['quux', 'corge', 'grault'])
arg = ['quux', 'corge', 'grault']
>>> x = mod.Foo()
>>> x
<mod.Foo object at 0x03C181F0>
```

[![](https://img.realpython.net/985664a6516083df6deee129c0591bfb)](https://srv.realpython.net/click/21785147887/?c=59166930991\&p=58946116052\&r=96792)[ Remove ads](https://realpython.com/account/join/)

### The Module Search Path

Continuing with the above example, let’s take a look at what happens when Python executes the statement:

```
import mod
```

When the interpreter executes the above `import` statement, it searches for `mod.py` in a [list](https://realpython.com/python-lists-tuples/) of directories assembled from the following sources:

* The directory from which the input script was run or the **current directory** if the interpreter is being run interactively
* The list of directories contained in the [`PYTHONPATH`](https://docs.python.org/3/using/cmdline.html#envvar-PYTHONPATH) environment variable, if it is set. (The format for `PYTHONPATH` is OS-dependent but should mimic the `PATH` environment variable.)
* An installation-dependent list of directories configured at the time Python is installed

The resulting search path is accessible in the Python variable `sys.path`, which is obtained from a module named `sys`:>>>

```
>>> import sys
>>> sys.path
['', 'C:\\Users\\john\\Documents\\Python\\doc', 'C:\\Python36\\Lib\\idlelib',
'C:\\Python36\\python36.zip', 'C:\\Python36\\DLLs', 'C:\\Python36\\lib',
'C:\\Python36', 'C:\\Python36\\lib\\site-packages']
```

**Note:** The exact contents of `sys.path` are installation-dependent. The above will almost certainly look slightly different on your computer.

Thus, to ensure your module is found, you need to do one of the following:

* Put `mod.py` in the directory where the input script is located or the **current directory**, if interactive
* Modify the `PYTHONPATH` environment variable to contain the directory where `mod.py` is located before starting the interpreter
  * **Or:** Put `mod.py` in one of the directories already contained in the `PYTHONPATH` variable
* Put `mod.py` in one of the installation-dependent directories, which you may or may not have write-access to, depending on the OS

There is actually one additional option: you can put the module file in any directory of your choice and then modify `sys.path` at run-time so that it contains that directory. For example, in this case, you could put `mod.py` in directory `C:\Users\john` and then issue the following statements:>>>

```
>>> sys.path.append(r'C:\Users\john')
>>> sys.path
['', 'C:\\Users\\john\\Documents\\Python\\doc', 'C:\\Python36\\Lib\\idlelib',
'C:\\Python36\\python36.zip', 'C:\\Python36\\DLLs', 'C:\\Python36\\lib',
'C:\\Python36', 'C:\\Python36\\lib\\site-packages', 'C:\\Users\\john']
>>> import mod
```

Once a module has been imported, you can determine the location where it was found with the module’s `__file__` attribute:>>>

```
>>> import mod
>>> mod.__file__
'C:\\Users\\john\\mod.py'

>>> import re
>>> re.__file__
'C:\\Python36\\lib\\re.py'
```

The directory portion of `__file__` should be one of the directories in `sys.path`.

### The `import` Statement

**Module** contents are made available to the caller with the `import` statement. The `import` statement takes many different forms, shown below.

#### `import <module_name>`

The simplest form is the one already shown above:

```
import <module_name>
```

Note that this *does not* make the module contents *directly* accessible to the caller. Each module has its own **private symbol table**, which serves as the global symbol table for all objects defined *in the module*. Thus, a module creates a separate **namespace**, as already noted.

The statement `import <module_name>` only places `<module_name>` in the caller’s symbol table. The *objects* that are defined in the module *remain in the module’s private symbol table*.

From the caller, objects in the module are only accessible when prefixed with `<module_name>` via **dot notation**, as illustrated below.

After the following `import` statement, `mod` is placed into the local symbol table. Thus, `mod` has meaning in the caller’s local context:>>>

```
>>> import mod
>>> mod
<module 'mod' from 'C:\\Users\\john\\Documents\\Python\\doc\\mod.py'>
```

But `s` and `foo` remain in the module’s private symbol table and are not meaningful in the local context:>>>

```
>>> s
NameError: name 's' is not defined
>>> foo('quux')
NameError: name 'foo' is not defined
```

To be accessed in the local context, names of objects defined in the module must be prefixed by `mod`:>>>

```
>>> mod.s
'If Comrade Napoleon says it, it must be right.'
>>> mod.foo('quux')
arg = quux
```

Several comma-separated modules may be specified in a single `import` statement:

```
import <module_name>[, <module_name> ...]
```

[![](https://img.realpython.net/ebb4fba61c1032b36fd97b803225bc8f)](https://srv.realpython.net/click/17294013797/?c=37584728541\&p=58946116052\&r=36663)[ Remove ads](https://realpython.com/account/join/)

#### `from <module_name> import <name(s)>`

An alternate form of the `import` statement allows individual objects from the module to be imported *directly into the caller’s symbol table*:

```
from <module_name> import <name(s)>
```

Following execution of the above statement, `<name(s)>` can be referenced in the caller’s environment without the `<module_name>` prefix:>>>

```
>>> from mod import s, foo
>>> s
'If Comrade Napoleon says it, it must be right.'
>>> foo('quux')
arg = quux

>>> from mod import Foo
>>> x = Foo()
>>> x
<mod.Foo object at 0x02E3AD50>
```

Because this form of `import` places the object names directly into the caller’s symbol table, any objects that already exist with the same name will be *overwritten*:>>>

```
>>> a = ['foo', 'bar', 'baz']
>>> a
['foo', 'bar', 'baz']

>>> from mod import a
>>> a
[100, 200, 300]
```

It is even possible to indiscriminately `import` everything from a module at one fell swoop:

```
from <module_name> import *
```

This will place the names of *all* objects from `<module_name>` into the local symbol table, with the exception of any that begin with the underscore (`_`) character.

For example:>>>

```
>>> from mod import *
>>> s
'If Comrade Napoleon says it, it must be right.'
>>> a
[100, 200, 300]
>>> foo
<function foo at 0x03B449C0>
>>> Foo
<class 'mod.Foo'>
```

This isn’t necessarily recommended in large-scale production code. It’s a bit dangerous because you are entering names into the local symbol table *en masse*. Unless you know them all well and can be confident there won’t be a conflict, you have a decent chance of overwriting an existing name inadvertently. However, this syntax is quite handy when you are just mucking around with the interactive interpreter, for testing or discovery purposes, because it quickly gives you access to everything a module has to offer without a lot of typing.

#### `from <module_name> import <name> as <alt_name>`

It is also possible to `import` individual objects but enter them into the local symbol table with alternate names:

```
from <module_name> import <name> as <alt_name>[, <name> as <alt_name> …]
```

This makes it possible to place names directly into the local symbol table but avoid conflicts with previously existing names:>>>

```
>>> s = 'foo'
>>> a = ['foo', 'bar', 'baz']

>>> from mod import s as string, a as alist
>>> s
'foo'
>>> string
'If Comrade Napoleon says it, it must be right.'
>>> a
['foo', 'bar', 'baz']
>>> alist
[100, 200, 300]
```

#### `import <module_name> as <alt_name>`

You can also import an entire module under an alternate name:

```
import <module_name> as <alt_name>
```

\>>>

```
>>> import mod as my_module
>>> my_module.a
[100, 200, 300]
>>> my_module.foo('qux')
arg = qux
```

Module contents can be imported from within a [function definition](https://realpython.com/defining-your-own-python-function/). In that case, the `import` does not occur until the function is *called*:>>>

```
>>> def bar():
...     from mod import foo
...     foo('corge')
...

>>> bar()
arg = corge
```

However, **Python 3** does not allow the indiscriminate `import *` syntax from within a function:>>>

```
>>> def bar():
...     from mod import *
...
SyntaxError: import * only allowed at module level
```

Lastly, a [`try` statement with an `except ImportError`](https://realpython.com/python-exceptions/) clause can be used to guard against unsuccessful `import` attempts:>>>

```
>>> try:
...     # Non-existent module
...     import baz
... except ImportError:
...     print('Module not found')
...

Module not found
```

\>>>

```
>>> try:
...     # Existing module, but non-existent object
...     from mod import baz
... except ImportError:
...     print('Object not found in module')
...

Object not found in module
```

[![](https://img.realpython.net/785012599729209d9a50c87329a69fbc)](https://srv.realpython.net/click/64251616254/?c=57731396368\&p=58946116052\&r=37348)[ Remove ads](https://realpython.com/account/join/)

### The `dir()` Function

The built-in function `dir()` returns a list of defined names in a namespace. Without arguments, it produces an alphabetically sorted list of names in the current **local symbol table**:>>>

```
>>> dir()
['__annotations__', '__builtins__', '__doc__', '__loader__', '__name__',
'__package__', '__spec__']

>>> qux = [1, 2, 3, 4, 5]
>>> dir()
['__annotations__', '__builtins__', '__doc__', '__loader__', '__name__',
'__package__', '__spec__', 'qux']

>>> class Bar():
...     pass
...
>>> x = Bar()
>>> dir()
['Bar', '__annotations__', '__builtins__', '__doc__', '__loader__', '__name__',
'__package__', '__spec__', 'qux', 'x']
```

Note how the first call to `dir()` above lists several names that are automatically defined and already in the namespace when the interpreter starts. As new names are defined (`qux`, `Bar`, `x`), they appear on subsequent invocations of `dir()`.

This can be useful for identifying what exactly has been added to the namespace by an import statement:>>>

```
>>> dir()
['__annotations__', '__builtins__', '__doc__', '__loader__', '__name__',
'__package__', '__spec__']

>>> import mod
>>> dir()
['__annotations__', '__builtins__', '__doc__', '__loader__', '__name__',
'__package__', '__spec__', 'mod']
>>> mod.s
'If Comrade Napoleon says it, it must be right.'
>>> mod.foo([1, 2, 3])
arg = [1, 2, 3]

>>> from mod import a, Foo
>>> dir()
['Foo', '__annotations__', '__builtins__', '__doc__', '__loader__', '__name__',
'__package__', '__spec__', 'a', 'mod']
>>> a
[100, 200, 300]
>>> x = Foo()
>>> x
<mod.Foo object at 0x002EAD50>

>>> from mod import s as string
>>> dir()
['Foo', '__annotations__', '__builtins__', '__doc__', '__loader__', '__name__',
'__package__', '__spec__', 'a', 'mod', 'string', 'x']
>>> string
'If Comrade Napoleon says it, it must be right.'
```

When given an argument that is the name of a module, `dir()` lists the names defined in the module:>>>

```
>>> import mod
>>> dir(mod)
['Foo', '__builtins__', '__cached__', '__doc__', '__file__', '__loader__',
'__name__', '__package__', '__spec__', 'a', 'foo', 's']
```

\>>>

```
>>> dir()
['__annotations__', '__builtins__', '__doc__', '__loader__', '__name__',
'__package__', '__spec__']
>>> from mod import *
>>> dir()
['Foo', '__annotations__', '__builtins__', '__doc__', '__loader__', '__name__',
'__package__', '__spec__', 'a', 'foo', 's']
```

### Executing a Module as a Script

Any `.py` file that contains a **module** is essentially also a Python **script**, and there isn’t any reason it can’t be executed like one.

Here again is `mod.py` as it was defined above:

***mod.py***

```
s = "If Comrade Napoleon says it, it must be right."
a = [100, 200, 300]

def foo(arg):
    print(f'arg = {arg}')

class Foo:
    pass
```

This can be run as a script:

```
C:\Users\john\Documents>python mod.py
C:\Users\john\Documents>
```

There are no errors, so it apparently worked. Granted, it’s not very interesting. As it is written, it only *defines* objects. It doesn’t *do* anything with them, and it doesn’t generate any output.

Let’s modify the above Python module so it does generate some output when run as a script:

***mod.py***

```
s = "If Comrade Napoleon says it, it must be right."
a = [100, 200, 300]

def foo(arg):
    print(f'arg = {arg}')

class Foo:
    pass

print(s)
print(a)
foo('quux')
x = Foo()
print(x)
```

Now it should be a little more interesting:

```
C:\Users\john\Documents>python mod.py
If Comrade Napoleon says it, it must be right.
[100, 200, 300]
arg = quux
<__main__.Foo object at 0x02F101D0>
```

Unfortunately, now it also generates output when imported as a module:>>>

```
>>> import mod
If Comrade Napoleon says it, it must be right.
[100, 200, 300]
arg = quux
<mod.Foo object at 0x0169AD50>
```

This is probably not what you want. It isn’t usual for a module to generate output when it is imported.

Wouldn’t it be nice if you could distinguish between when the file is loaded as a module and when it is run as a standalone script?

Ask and ye shall receive.

When a `.py` file is imported as a module, Python sets the special **dunder** variable [`__name__`](https://realpython.com/python-main-function/) to the name of the module. However, if a file is run as a standalone script, `__name__` is (creatively) set to the string `'__main__'`. Using this fact, you can discern which is the case at run-time and alter behavior accordingly:

***mod.py***

```
s = "If Comrade Napoleon says it, it must be right."
a = [100, 200, 300]

def foo(arg):
    print(f'arg = {arg}')

class Foo:
    pass

if (__name__ == '__main__'):
    print('Executing as standalone script')
    print(s)
    print(a)
    foo('quux')
    x = Foo()
    print(x)
```

Now, if you run as a script, you get output:

```
C:\Users\john\Documents>python mod.py
Executing as standalone script
If Comrade Napoleon says it, it must be right.
[100, 200, 300]
arg = quux
<__main__.Foo object at 0x03450690>
```

But if you import as a module, you don’t:>>>

```
>>> import mod
>>> mod.foo('grault')
arg = grault
```

Modules are often designed with the capability to run as a standalone script for purposes of testing the functionality that is contained within the module. This is referred to as [**unit testing**](https://realpython.com/python-testing/)**.** For example, suppose you have created a module `fact.py` containing a **factorial** function, as follows:

***fact.py***

```
def fact(n):
    return 1 if n == 1 else n * fact(n-1)

if (__name__ == '__main__'):
    import sys
    if len(sys.argv) > 1:
        print(fact(int(sys.argv[1])))
```

The file can be treated as a module, and the `fact()` function imported:>>>

```
>>> from fact import fact
>>> fact(6)
720
```

But it can also be run as a standalone by passing an integer argument on the command-line for testing:

```
C:\Users\john\Documents>python fact.py 6
720
```

[![](https://img.realpython.net/7915ae1c65bffcd60287b05a4a5e2d20)](https://srv.realpython.net/click/59335905319/?c=32419346518\&p=58946116052\&r=67094)[ Remove ads](https://realpython.com/account/join/)

### Reloading a Module

For reasons of efficiency, a module is only loaded once per interpreter session. That is fine for function and class definitions, which typically make up the bulk of a module’s contents. But a module can contain executable statements as well, usually for initialization. Be aware that these statements will only be executed the *first time* a module is imported.

Consider the following file `mod.py`:

***mod.py***

```
a = [100, 200, 300]
print('a =', a)
```

\>>>

```
>>> import mod
a = [100, 200, 300]
>>> import mod
>>> import mod

>>> mod.a
[100, 200, 300]
```

The `print()` statement is not executed on subsequent imports. (For that matter, neither is the assignment statement, but as the final display of the value of `mod.a` shows, that doesn’t matter. Once the assignment is made, it sticks.)

If you make a change to a module and need to reload it, you need to either restart the interpreter or use a function called `reload()` from module `importlib`:>>>

```
>>> import mod
a = [100, 200, 300]

>>> import mod

>>> import importlib
>>> importlib.reload(mod)
a = [100, 200, 300]
<module 'mod' from 'C:\\Users\\john\\Documents\\Python\\doc\\mod.py'>
```

### Python Packages

Suppose you have developed a very large application that includes many modules. As the number of modules grows, it becomes difficult to keep track of them all if they are dumped into one location. This is particularly so if they have similar names or functionality. You might wish for a means of grouping and organizing them.

**Packages** allow for a hierarchical structuring of the module namespace using **dot notation**. In the same way that **modules** help avoid collisions between global variable names, **packages** help avoid collisions between module names.

Creating a **package** is quite straightforward, since it makes use of the operating system’s inherent hierarchical file structure. Consider the following arrangement:[![Image of a Python package](https://files.realpython.com/media/pkg1.9af1c7aea48f.png)](https://files.realpython.com/media/pkg1.9af1c7aea48f.png)

Here, there is a directory named `pkg` that contains two modules, `mod1.py` and `mod2.py`. The contents of the modules are:

***mod1.py***

```
def foo():
    print('[mod1] foo()')

class Foo:
    pass
```

***mod2.py***

```
def bar():
    print('[mod2] bar()')

class Bar:
    pass
```

Given this structure, if the `pkg` directory resides in a location where it can be found (in one of the directories contained in `sys.path`), you can refer to the two **modules** with **dot notation** (`pkg.mod1`, `pkg.mod2`) and import them with the syntax you are already familiar with:

```
import <module_name>[, <module_name> ...]
```

\>>>

```
>>> import pkg.mod1, pkg.mod2
>>> pkg.mod1.foo()
[mod1] foo()
>>> x = pkg.mod2.Bar()
>>> x
<pkg.mod2.Bar object at 0x033F7290>
```

```
from <module_name> import <name(s)>
```

\>>>

```
>>> from pkg.mod1 import foo
>>> foo()
[mod1] foo()
```

```
from <module_name> import <name> as <alt_name>
```

\>>>

```
>>> from pkg.mod2 import Bar as Qux
>>> x = Qux()
>>> x
<pkg.mod2.Bar object at 0x036DFFD0>
```

You can import modules with these statements as well:

```
from <package_name> import <modules_name>[, <module_name> ...]
from <package_name> import <module_name> as <alt_name>
```

\>>>

```
>>> from pkg import mod1
>>> mod1.foo()
[mod1] foo()

>>> from pkg import mod2 as quux
>>> quux.bar()
[mod2] bar()
```

You can technically import the package as well:>>>

```
>>> import pkg
>>> pkg
<module 'pkg' (namespace)>
```

But this is of little avail. Though this is, strictly speaking, a syntactically correct Python statement, it doesn’t do much of anything useful. In particular, it *does not place* any of the modules in `pkg` into the local namespace:>>>

```
>>> pkg.mod1
Traceback (most recent call last):
  File "<pyshell#34>", line 1, in <module>
    pkg.mod1
AttributeError: module 'pkg' has no attribute 'mod1'
>>> pkg.mod1.foo()
Traceback (most recent call last):
  File "<pyshell#35>", line 1, in <module>
    pkg.mod1.foo()
AttributeError: module 'pkg' has no attribute 'mod1'
>>> pkg.mod2.Bar()
Traceback (most recent call last):
  File "<pyshell#36>", line 1, in <module>
    pkg.mod2.Bar()
AttributeError: module 'pkg' has no attribute 'mod2'
```

To actually import the modules or their contents, you need to use one of the forms shown above.[![](https://img.realpython.net/ce045944865116e7c70acc217eac34ec)](https://srv.realpython.net/click/12410455494/?c=13641354227\&p=58946116052\&r=89494)[ Remove ads](https://realpython.com/account/join/)

### Package Initialization

If a file named `__init__.py` is present in a package directory, it is invoked when the package or a module in the package is imported. This can be used for execution of package initialization code, such as initialization of package-level data.

For example, consider the following `__init__.py` file:

***\_\_init\_\_.py***

```
print(f'Invoking __init__.py for {__name__}')
A = ['quux', 'corge', 'grault']
```

Let’s add this file to the `pkg` directory from the above example:[![Illustration of hierarchical file structure of Python packages](https://files.realpython.com/media/pkg2.dab97c2f9c58.png)](https://files.realpython.com/media/pkg2.dab97c2f9c58.png)

Now when the package is imported, the global list `A` is initialized:>>>

```
>>> import pkg
Invoking __init__.py for pkg
>>> pkg.A
['quux', 'corge', 'grault']
```

A **module** in the package can access the global variable by importing it in turn:

***mod1.py***

```
def foo():
    from pkg import A
    print('[mod1] foo() / A = ', A)

class Foo:
    pass
```

\>>>

```
>>> from pkg import mod1
Invoking __init__.py for pkg
>>> mod1.foo()
[mod1] foo() / A =  ['quux', 'corge', 'grault']
```

`__init__.py` can also be used to effect automatic importing of modules from a package. For example, earlier you saw that the statement `import pkg` only places the name `pkg` in the caller’s local symbol table and doesn’t import any modules. But if `__init__.py` in the `pkg` directory contains the following:

***\_\_init\_\_.py***

```
print(f'Invoking __init__.py for {__name__}')
import pkg.mod1, pkg.mod2
```

then when you execute `import pkg`, modules `mod1` and `mod2` are imported automatically:>>>

```
>>> import pkg
Invoking __init__.py for pkg
>>> pkg.mod1.foo()
[mod1] foo()
>>> pkg.mod2.bar()
[mod2] bar()
```

**Note:** Much of the Python documentation states that an `__init__.py` file **must** be present in the package directory when creating a package. This was once true. It used to be that the very presence of `__init__.py` signified to Python that a package was being defined. The file could contain initialization code or even be empty, but it **had** to be present.

Starting with **Python 3.3**, [Implicit Namespace Packages](https://www.python.org/dev/peps/pep-0420) were introduced. These allow for the creation of a package without any `__init__.py` file. Of course, it **can** still be present if package initialization is needed. But it is no longer required.

### Importing `*` From a Package

For the purposes of the following discussion, the previously defined package is expanded to contain some additional modules:[![Illustration of hierarchical file structure of Python packages](https://files.realpython.com/media/pkg3.d2160908ae77.png)](https://files.realpython.com/media/pkg3.d2160908ae77.png)

There are now four modules defined in the `pkg` directory. Their contents are as shown below:

***mod1.py***

```
def foo():
    print('[mod1] foo()')

class Foo:
    pass
```

***mod2.py***

```
def bar():
    print('[mod2] bar()')

class Bar:
    pass
```

***mod3.py***

```
def baz():
    print('[mod3] baz()')

class Baz:
    pass
```

***mod4.py***

```
def qux():
    print('[mod4] qux()')

class Qux:
    pass
```

(Imaginative, aren’t they?)

You have already seen that when `import *` is used for a **module**, *all* objects from the module are imported into the local symbol table, except those whose names begin with an underscore, as always:>>>

```
>>> dir()
['__annotations__', '__builtins__', '__doc__', '__loader__', '__name__',
'__package__', '__spec__']

>>> from pkg.mod3 import *

>>> dir()
['Baz', '__annotations__', '__builtins__', '__doc__', '__loader__', '__name__',
'__package__', '__spec__', 'baz']
>>> baz()
[mod3] baz()
>>> Baz
<class 'pkg.mod3.Baz'>
```

The analogous statement for a **package** is this:

```
from <package_name> import *
```

What does that do?>>>

```
>>> dir()
['__annotations__', '__builtins__', '__doc__', '__loader__', '__name__',
'__package__', '__spec__']

>>> from pkg import *
>>> dir()
['__annotations__', '__builtins__', '__doc__', '__loader__', '__name__',
'__package__', '__spec__']
```

Hmph. Not much. You might have expected (assuming you had any expectations at all) that Python would dive down into the package directory, find all the modules it could, and import them all. But as you can see, by default that is not what happens.

Instead, Python follows this convention: if the `__init__.py` file in the **package** directory contains a **list** named `__all__`, it is taken to be a list of modules that should be imported when the statement `from <package_name> import *` is encountered.

For the present example, suppose you create an `__init__.py` in the `pkg` directory like this:

***pkg/\_\_init\_\_.py***

```
__all__ = [
        'mod1',
        'mod2',
        'mod3',
        'mod4'
        ]
```

Now `from pkg import *` imports all four modules:>>>

```
>>> dir()
['__annotations__', '__builtins__', '__doc__', '__loader__', '__name__',
'__package__', '__spec__']

>>> from pkg import *
>>> dir()
['__annotations__', '__builtins__', '__doc__', '__loader__', '__name__',
'__package__', '__spec__', 'mod1', 'mod2', 'mod3', 'mod4']
>>> mod2.bar()
[mod2] bar()
>>> mod4.Qux
<class 'pkg.mod4.Qux'>
```

Using `import *` still isn’t considered terrific form, any more for **packages** than for **modules**. But this facility at least gives the creator of the package some control over what happens when `import *` is specified. (In fact, it provides the capability to disallow it entirely, simply by declining to define `__all__` at all. As you have seen, the default behavior for packages is to import nothing.)

By the way, `__all__` can be defined in a **module** as well and serves the same purpose: to control what is imported with `import *`. For example, modify `mod1.py` as follows:

***pkg/mod1.py***

```
__all__ = ['foo']

def foo():
    print('[mod1] foo()')

class Foo:
    pass
```

Now an `import *` statement from `pkg.mod1` will only import what is contained in `__all__`:>>>

```
>>> dir()
['__annotations__', '__builtins__', '__doc__', '__loader__', '__name__',
'__package__', '__spec__']

>>> from pkg.mod1 import *
>>> dir()
['__annotations__', '__builtins__', '__doc__', '__loader__', '__name__',
'__package__', '__spec__', 'foo']

>>> foo()
[mod1] foo()
>>> Foo
Traceback (most recent call last):
  File "<pyshell#37>", line 1, in <module>
    Foo
NameError: name 'Foo' is not defined
```

`foo()` (the function) is now defined in the local namespace, but `Foo` (the class) is not, because the latter is not in `__all__`.

In summary, `__all__` is used by both **packages** and **modules** to control what is imported when `import *` is specified. But *the default behavior differs*:

* For a package, when `__all__` is not defined, `import *` does not import anything.
* For a module, when `__all__` is not defined, `import *` imports everything (except—you guessed it—names starting with an underscore).

[![](https://img.realpython.net/16bf1efe41b538fae54711c58c701f0e)](https://srv.realpython.net/click/58257184031/?c=31941813441\&p=58946116052\&r=17046)[ Remove ads](https://realpython.com/account/join/)

### Subpackages

Packages can contain nested **subpackages** to arbitrary depth. For example, let’s make one more modification to the example **package** directory as follows:[![Illustration of hierarchical file structure of Python packages](https://files.realpython.com/media/pkg4.a830d6e144bf.png)](https://files.realpython.com/media/pkg4.a830d6e144bf.png)

The four modules (`mod1.py`, `mod2.py`, `mod3.py` and `mod4.py`) are defined as previously. But now, instead of being lumped together into the `pkg` directory, they are split out into two **subpackage** directories, `sub_pkg1` and `sub_pkg2`.

Importing still works the same as shown previously. Syntax is similar, but additional **dot notation** is used to separate **package** name from **subpackage** name:>>>

```
>>> import pkg.sub_pkg1.mod1
>>> pkg.sub_pkg1.mod1.foo()
[mod1] foo()

>>> from pkg.sub_pkg1 import mod2
>>> mod2.bar()
[mod2] bar()

>>> from pkg.sub_pkg2.mod3 import baz
>>> baz()
[mod3] baz()

>>> from pkg.sub_pkg2.mod4 import qux as grault
>>> grault()
[mod4] qux()
```

In addition, a module in one **subpackage** can reference objects in a **sibling subpackage** (in the event that the sibling contains some functionality that you need). For example, suppose you want to import and execute function `foo()` (defined in module `mod1`) from within module `mod3`. You can either use an **absolute import**:

***pkg/sub\_\_pkg2/mod3.py***

```
def baz():
    print('[mod3] baz()')

class Baz:
    pass

from pkg.sub_pkg1.mod1 import foo
foo()
```

\>>>

```
>>> from pkg.sub_pkg2 import mod3
[mod1] foo()
>>> mod3.foo()
[mod1] foo()
```

Or you can use a **relative import**, where `..` refers to the package one level up. From within `mod3.py`, which is in subpackage `sub_pkg2`,

* `..` evaluates to the parent package (`pkg`), and
* `..sub_pkg1` evaluates to subpackage `sub_pkg1` of the parent package.

***pkg/sub\_\_pkg2/mod3.py***

```
def baz():
    print('[mod3] baz()')

class Baz:
    pass

from .. import sub_pkg1
print(sub_pkg1)

from ..sub_pkg1.mod1 import foo
foo()
```

\>>>

```
>>> from pkg.sub_pkg2 import mod3
<module 'pkg.sub_pkg1' (namespace)>
[mod1] foo()
```

### Conclusion

In this tutorial, you covered the following topics:

* How to create a Python **module**
* Locations where the Python interpreter searches for a module
* How to obtain access to the objects defined in a module with the `import` statement
* How to create a module that is executable as a standalone script
* How to organize modules into **packages** and **subpackages**
* How to control package initialization

**Free PDF Download:** [Python 3 Cheat Sheet](https://realpython.com/bonus/python-cheat-sheet-short/)

This will hopefully allow you to better understand how to gain access to the functionality available in the many third-party and built-in modules available in Python.

Additionally, if you are developing your own application, creating your own **modules** and **packages** will help you organize and modularize your code, which makes coding, maintenance, and debugging easier.

If you want to learn more, check out the following documentation at **Python.org**:

## [`__main__`](https://docs.python.org/3/library/__main__.html#module-__main__) — Top-level script environment

`'__main__'` is the name of the scope in which top-level code executes. A module’s \_\_name\_\_ is set equal to `'__main__'` when read from standard input, a script, or from an interactive prompt.

A module can discover whether or not it is running in the main scope by checking its own `__name__`, which allows a common idiom for conditionally executing code in a module when it is run as a script or with `python -m` but not when it is imported:

```
if __name__ == "__main__":
    # execute only if run as a script
    main()
```

For a package, the same effect can be achieved by including a `__main__.py` module, the contents of which will be executed when the module is run

## . The import system

Python code in one [module](https://docs.python.org/3/glossary.html#term-module) gains access to the code in another module by the process of [importing](https://docs.python.org/3/glossary.html#term-importing) it. The [`import`](https://docs.python.org/3/reference/simple_stmts.html#import) statement is the most common way of invoking the import machinery, but it is not the only way. Functions such as [`importlib.import_module()`](https://docs.python.org/3/library/importlib.html#importlib.import_module) and built-in [`__import__()`](https://docs.python.org/3/library/functions.html#__import__) can also be used to invoke the import machinery.

The [`import`](https://docs.python.org/3/reference/simple_stmts.html#import) statement combines two operations; it searches for the named module, then it binds the results of that search to a name in the local scope. The search operation of the `import` statement is defined as a call to the [`__import__()`](https://docs.python.org/3/library/functions.html#__import__) function, with the appropriate arguments. The return value of [`__import__()`](https://docs.python.org/3/library/functions.html#__import__) is used to perform the name binding operation of the `import` statement. See the `import` statement for the exact details of that name binding operation.

A direct call to [`__import__()`](https://docs.python.org/3/library/functions.html#__import__) performs only the module search and, if found, the module creation operation. While certain side-effects may occur, such as the importing of parent packages, and the updating of various caches (including [`sys.modules`](https://docs.python.org/3/library/sys.html#sys.modules)), only the [`import`](https://docs.python.org/3/reference/simple_stmts.html#import) statement performs a name binding operation.

When an [`import`](https://docs.python.org/3/reference/simple_stmts.html#import) statement is executed, the standard builtin [`__import__()`](https://docs.python.org/3/library/functions.html#__import__) function is called. Other mechanisms for invoking the import system (such as [`importlib.import_module()`](https://docs.python.org/3/library/importlib.html#importlib.import_module)) may choose to bypass [`__import__()`](https://docs.python.org/3/library/functions.html#__import__) and use their own solutions to implement import semantics.

When a module is first imported, Python searches for the module and if found, it creates a module object [1](https://docs.python.org/3/reference/import.html#fnmo), initializing it. If the named module cannot be found, a [`ModuleNotFoundError`](https://docs.python.org/3/library/exceptions.html#ModuleNotFoundError) is raised. Python implements various strategies to search for the named module when the import machinery is invoked. These strategies can be modified and extended by using various hooks described in the sections below.

Changed in version 3.3: The import system has been updated to fully implement the second phase of [**PEP 302**](https://www.python.org/dev/peps/pep-0302). There is no longer any implicit import machinery - the full import system is exposed through [`sys.meta_path`](https://docs.python.org/3/library/sys.html#sys.meta_path). In addition, native namespace package support has been implemented (see [**PEP 420**](https://www.python.org/dev/peps/pep-0420)).

### 5.1. [`importlib`](https://docs.python.org/3/library/importlib.html#module-importlib)

The [`importlib`](https://docs.python.org/3/library/importlib.html#module-importlib) module provides a rich API for interacting with the import system. For example [`importlib.import_module()`](https://docs.python.org/3/library/importlib.html#importlib.import_module) provides a recommended, simpler API than built-in [`__import__()`](https://docs.python.org/3/library/functions.html#__import__) for invoking the import machinery. Refer to the [`importlib`](https://docs.python.org/3/library/importlib.html#module-importlib) library documentation for additional detail.

### 5.2. Packages

Python has only one type of module object, and all modules are of this type, regardless of whether the module is implemented in Python, C, or something else. To help organize modules and provide a naming hierarchy, Python has a concept of [packages](https://docs.python.org/3/glossary.html#term-package).

You can think of packages as the directories on a file system and modules as files within directories, but don’t take this analogy too literally since packages and modules need not originate from the file system. For the purposes of this documentation, we’ll use this convenient analogy of directories and files. Like file system directories, packages are organized hierarchically, and packages may themselves contain subpackages, as well as regular modules.

It’s important to keep in mind that all packages are modules, but not all modules are packages. Or put another way, packages are just a special kind of module. Specifically, any module that contains a `__path__` attribute is considered a package.

All modules have a name. Subpackage names are separated from their parent package name by a dot, akin to Python’s standard attribute access syntax. Thus you might have a module called [`sys`](https://docs.python.org/3/library/sys.html#module-sys) and a package called [`email`](https://docs.python.org/3/library/email.html#module-email), which in turn has a subpackage called [`email.mime`](https://docs.python.org/3/library/email.mime.html#module-email.mime) and a module within that subpackage called `email.mime.text`.

#### 5.2.1. Regular packages

Python defines two types of packages, [regular packages](https://docs.python.org/3/glossary.html#term-regular-package) and [namespace packages](https://docs.python.org/3/glossary.html#term-namespace-package). Regular packages are traditional packages as they existed in Python 3.2 and earlier. A regular package is typically implemented as a directory containing an `__init__.py` file. When a regular package is imported, this `__init__.py` file is implicitly executed, and the objects it defines are bound to names in the package’s namespace. The `__init__.py` file can contain the same Python code that any other module can contain, and Python will add some additional attributes to the module when it is imported.

For example, the following file system layout defines a top level `parent` package with three subpackages:

```
parent/
    __init__.py
    one/
        __init__.py
    two/
        __init__.py
    three/
        __init__.py
```

Importing `parent.one` will implicitly execute `parent/__init__.py` and `parent/one/__init__.py`. Subsequent imports of `parent.two` or `parent.three` will execute `parent/two/__init__.py` and `parent/three/__init__.py` respectively.

#### 5.2.2. Namespace packages

A namespace package is a composite of various [portions](https://docs.python.org/3/glossary.html#term-portion), where each portion contributes a subpackage to the parent package. Portions may reside in different locations on the file system. Portions may also be found in zip files, on the network, or anywhere else that Python searches during import. Namespace packages may or may not correspond directly to objects on the file system; they may be virtual modules that have no concrete representation.

Namespace packages do not use an ordinary list for their `__path__` attribute. They instead use a custom iterable type which will automatically perform a new search for package portions on the next import attempt within that package if the path of their parent package (or [`sys.path`](https://docs.python.org/3/library/sys.html#sys.path) for a top level package) changes.

With namespace packages, there is no `parent/__init__.py` file. In fact, there may be multiple `parent` directories found during import search, where each one is provided by a different portion. Thus `parent/one` may not be physically located next to `parent/two`. In this case, Python will create a namespace package for the top-level `parent` package whenever it or one of its subpackages is imported.

See also [**PEP 420**](https://www.python.org/dev/peps/pep-0420) for the namespace package specification.

### 5.3. Searching

To begin the search, Python needs the [fully qualified](https://docs.python.org/3/glossary.html#term-qualified-name) name of the module (or package, but for the purposes of this discussion, the difference is immaterial) being imported. This name may come from various arguments to the [`import`](https://docs.python.org/3/reference/simple_stmts.html#import) statement, or from the parameters to the [`importlib.import_module()`](https://docs.python.org/3/library/importlib.html#importlib.import_module) or [`__import__()`](https://docs.python.org/3/library/functions.html#__import__) functions.

This name will be used in various phases of the import search, and it may be the dotted path to a submodule, e.g. `foo.bar.baz`. In this case, Python first tries to import `foo`, then `foo.bar`, and finally `foo.bar.baz`. If any of the intermediate imports fail, a [`ModuleNotFoundError`](https://docs.python.org/3/library/exceptions.html#ModuleNotFoundError) is raised.

#### 5.3.1. The module cache

The first place checked during import search is [`sys.modules`](https://docs.python.org/3/library/sys.html#sys.modules). This mapping serves as a cache of all modules that have been previously imported, including the intermediate paths. So if `foo.bar.baz` was previously imported, [`sys.modules`](https://docs.python.org/3/library/sys.html#sys.modules) will contain entries for `foo`, `foo.bar`, and `foo.bar.baz`. Each key will have as its value the corresponding module object.

During import, the module name is looked up in [`sys.modules`](https://docs.python.org/3/library/sys.html#sys.modules) and if present, the associated value is the module satisfying the import, and the process completes. However, if the value is `None`, then a [`ModuleNotFoundError`](https://docs.python.org/3/library/exceptions.html#ModuleNotFoundError) is raised. If the module name is missing, Python will continue searching for the module.

[`sys.modules`](https://docs.python.org/3/library/sys.html#sys.modules) is writable. Deleting a key may not destroy the associated module (as other modules may hold references to it), but it will invalidate the cache entry for the named module, causing Python to search anew for the named module upon its next import. The key can also be assigned to `None`, forcing the next import of the module to result in a [`ModuleNotFoundError`](https://docs.python.org/3/library/exceptions.html#ModuleNotFoundError).

Beware though, as if you keep a reference to the module object, invalidate its cache entry in [`sys.modules`](https://docs.python.org/3/library/sys.html#sys.modules), and then re-import the named module, the two module objects will *not* be the same. By contrast, [`importlib.reload()`](https://docs.python.org/3/library/importlib.html#importlib.reload) will reuse the *same* module object, and simply reinitialise the module contents by rerunning the module’s code.

#### 5.3.2. Finders and loaders

If the named module is not found in [`sys.modules`](https://docs.python.org/3/library/sys.html#sys.modules), then Python’s import protocol is invoked to find and load the module. This protocol consists of two conceptual objects, [finders](https://docs.python.org/3/glossary.html#term-finder) and [loaders](https://docs.python.org/3/glossary.html#term-loader). A finder’s job is to determine whether it can find the named module using whatever strategy it knows about. Objects that implement both of these interfaces are referred to as [importers](https://docs.python.org/3/glossary.html#term-importer) - they return themselves when they find that they can load the requested module.

Python includes a number of default finders and importers. The first one knows how to locate built-in modules, and the second knows how to locate frozen modules. A third default finder searches an [import path](https://docs.python.org/3/glossary.html#term-import-path) for modules. The [import path](https://docs.python.org/3/glossary.html#term-import-path) is a list of locations that may name file system paths or zip files. It can also be extended to search for any locatable resource, such as those identified by URLs.

The import machinery is extensible, so new finders can be added to extend the range and scope of module searching.

Finders do not actually load modules. If they can find the named module, they return a *module spec*, an encapsulation of the module’s import-related information, which the import machinery then uses when loading the module.

The following sections describe the protocol for finders and loaders in more detail, including how you can create and register new ones to extend the import machinery.

Changed in version 3.4: In previous versions of Python, finders returned [loaders](https://docs.python.org/3/glossary.html#term-loader) directly, whereas now they return module specs which *contain* loaders. Loaders are still used during import but have fewer responsibilities.

#### 5.3.3. Import hooks

The import machinery is designed to be extensible; the primary mechanism for this are the *import hooks*. There are two types of import hooks: *meta hooks* and *import path hooks*.

Meta hooks are called at the start of import processing, before any other import processing has occurred, other than [`sys.modules`](https://docs.python.org/3/library/sys.html#sys.modules) cache look up. This allows meta hooks to override [`sys.path`](https://docs.python.org/3/library/sys.html#sys.path) processing, frozen modules, or even built-in modules. Meta hooks are registered by adding new finder objects to [`sys.meta_path`](https://docs.python.org/3/library/sys.html#sys.meta_path), as described below.

Import path hooks are called as part of [`sys.path`](https://docs.python.org/3/library/sys.html#sys.path) (or `package.__path__`) processing, at the point where their associated path item is encountered. Import path hooks are registered by adding new callables to [`sys.path_hooks`](https://docs.python.org/3/library/sys.html#sys.path_hooks) as described below.

#### 5.3.4. The meta path

When the named module is not found in [`sys.modules`](https://docs.python.org/3/library/sys.html#sys.modules), Python next searches [`sys.meta_path`](https://docs.python.org/3/library/sys.html#sys.meta_path), which contains a list of meta path finder objects. These finders are queried in order to see if they know how to handle the named module. Meta path finders must implement a method called [`find_spec()`](https://docs.python.org/3/library/importlib.html#importlib.abc.MetaPathFinder.find_spec) which takes three arguments: a name, an import path, and (optionally) a target module. The meta path finder can use any strategy it wants to determine whether it can handle the named module or not.

If the meta path finder knows how to handle the named module, it returns a spec object. If it cannot handle the named module, it returns `None`. If [`sys.meta_path`](https://docs.python.org/3/library/sys.html#sys.meta_path) processing reaches the end of its list without returning a spec, then a [`ModuleNotFoundError`](https://docs.python.org/3/library/exceptions.html#ModuleNotFoundError) is raised. Any other exceptions raised are simply propagated up, aborting the import process.

The [`find_spec()`](https://docs.python.org/3/library/importlib.html#importlib.abc.MetaPathFinder.find_spec) method of meta path finders is called with two or three arguments. The first is the fully qualified name of the module being imported, for example `foo.bar.baz`. The second argument is the path entries to use for the module search. For top-level modules, the second argument is `None`, but for submodules or subpackages, the second argument is the value of the parent package’s `__path__` attribute. If the appropriate `__path__` attribute cannot be accessed, a [`ModuleNotFoundError`](https://docs.python.org/3/library/exceptions.html#ModuleNotFoundError) is raised. The third argument is an existing module object that will be the target of loading later. The import system passes in a target module only during reload.

The meta path may be traversed multiple times for a single import request. For example, assuming none of the modules involved has already been cached, importing `foo.bar.baz` will first perform a top level import, calling `mpf.find_spec("foo", None, None)` on each meta path finder (`mpf`). After `foo` has been imported, `foo.bar` will be imported by traversing the meta path a second time, calling `mpf.find_spec("foo.bar", foo.__path__, None)`. Once `foo.bar` has been imported, the final traversal will call `mpf.find_spec("foo.bar.baz", foo.bar.__path__, None)`.

Some meta path finders only support top level imports. These importers will always return `None` when anything other than `None` is passed as the second argument.

Python’s default [`sys.meta_path`](https://docs.python.org/3/library/sys.html#sys.meta_path) has three meta path finders, one that knows how to import built-in modules, one that knows how to import frozen modules, and one that knows how to import modules from an [import path](https://docs.python.org/3/glossary.html#term-import-path) (i.e. the [path based finder](https://docs.python.org/3/glossary.html#term-path-based-finder)).

Changed in version 3.4: The [`find_spec()`](https://docs.python.org/3/library/importlib.html#importlib.abc.MetaPathFinder.find_spec) method of meta path finders replaced [`find_module()`](https://docs.python.org/3/library/importlib.html#importlib.abc.MetaPathFinder.find_module), which is now deprecated. While it will continue to work without change, the import machinery will try it only if the finder does not implement `find_spec()`.

### 5.4. Loading

If and when a module spec is found, the import machinery will use it (and the loader it contains) when loading the module. Here is an approximation of what happens during the loading portion of import:

```
module = None
if spec.loader is not None and hasattr(spec.loader, 'create_module'):
    # It is assumed 'exec_module' will also be defined on the loader.
    module = spec.loader.create_module(spec)
if module is None:
    module = ModuleType(spec.name)
# The import-related module attributes get set here:
_init_module_attrs(spec, module)

if spec.loader is None:
    # unsupported
    raise ImportError
if spec.origin is None and spec.submodule_search_locations is not None:
    # namespace package
    sys.modules[spec.name] = module
elif not hasattr(spec.loader, 'exec_module'):
    module = spec.loader.load_module(spec.name)
    # Set __loader__ and __package__ if missing.
else:
    sys.modules[spec.name] = module
    try:
        spec.loader.exec_module(module)
    except BaseException:
        try:
            del sys.modules[spec.name]
        except KeyError:
            pass
        raise
return sys.modules[spec.name]
```

Note the following details:

> * If there is an existing module object with the given name in [`sys.modules`](https://docs.python.org/3/library/sys.html#sys.modules), import will have already returned it.
> * The module will exist in [`sys.modules`](https://docs.python.org/3/library/sys.html#sys.modules) before the loader executes the module code. This is crucial because the module code may (directly or indirectly) import itself; adding it to [`sys.modules`](https://docs.python.org/3/library/sys.html#sys.modules) beforehand prevents unbounded recursion in the worst case and multiple loading in the best.
> * If loading fails, the failing module – and only the failing module – gets removed from [`sys.modules`](https://docs.python.org/3/library/sys.html#sys.modules). Any module already in the [`sys.modules`](https://docs.python.org/3/library/sys.html#sys.modules) cache, and any module that was successfully loaded as a side-effect, must remain in the cache. This contrasts with reloading where even the failing module is left in [`sys.modules`](https://docs.python.org/3/library/sys.html#sys.modules).
> * After the module is created but before execution, the import machinery sets the import-related module attributes (“\_init\_module\_attrs” in the pseudo-code example above), as summarized in a [later section](https://docs.python.org/3/reference/import.html#import-mod-attrs).
> * Module execution is the key moment of loading in which the module’s namespace gets populated. Execution is entirely delegated to the loader, which gets to decide what gets populated and how.
> * The module created during loading and passed to exec\_module() may not be the one returned at the end of import [2](https://docs.python.org/3/reference/import.html#fnlo).

Changed in version 3.4: The import system has taken over the boilerplate responsibilities of loaders. These were previously performed by the [`importlib.abc.Loader.load_module()`](https://docs.python.org/3/library/importlib.html#importlib.abc.Loader.load_module) method.

#### 5.4.1. Loaders

Module loaders provide the critical function of loading: module execution. The import machinery calls the [`importlib.abc.Loader.exec_module()`](https://docs.python.org/3/library/importlib.html#importlib.abc.Loader.exec_module) method with a single argument, the module object to execute. Any value returned from [`exec_module()`](https://docs.python.org/3/library/importlib.html#importlib.abc.Loader.exec_module) is ignored.

Loaders must satisfy the following requirements:

> * If the module is a Python module (as opposed to a built-in module or a dynamically loaded extension), the loader should execute the module’s code in the module’s global name space (`module.__dict__`).
> * If the loader cannot execute the module, it should raise an [`ImportError`](https://docs.python.org/3/library/exceptions.html#ImportError), although any other exception raised during [`exec_module()`](https://docs.python.org/3/library/importlib.html#importlib.abc.Loader.exec_module) will be propagated.

In many cases, the finder and loader can be the same object; in such cases the [`find_spec()`](https://docs.python.org/3/library/importlib.html#importlib.abc.MetaPathFinder.find_spec) method would just return a spec with the loader set to `self`.

Module loaders may opt in to creating the module object during loading by implementing a [`create_module()`](https://docs.python.org/3/library/importlib.html#importlib.abc.Loader.create_module) method. It takes one argument, the module spec, and returns the new module object to use during loading. `create_module()` does not need to set any attributes on the module object. If the method returns `None`, the import machinery will create the new module itself.

New in version 3.4: The [`create_module()`](https://docs.python.org/3/library/importlib.html#importlib.abc.Loader.create_module) method of loaders.

Changed in version 3.4: The [`load_module()`](https://docs.python.org/3/library/importlib.html#importlib.abc.Loader.load_module) method was replaced by [`exec_module()`](https://docs.python.org/3/library/importlib.html#importlib.abc.Loader.exec_module) and the import machinery assumed all the boilerplate responsibilities of loading.

For compatibility with existing loaders, the import machinery will use the `load_module()` method of loaders if it exists and the loader does not also implement `exec_module()`. However, `load_module()` has been deprecated and loaders should implement `exec_module()` instead.

The `load_module()` method must implement all the boilerplate loading functionality described above in addition to executing the module. All the same constraints apply, with some additional clarification:

> * If there is an existing module object with the given name in [`sys.modules`](https://docs.python.org/3/library/sys.html#sys.modules), the loader must use that existing module. (Otherwise, [`importlib.reload()`](https://docs.python.org/3/library/importlib.html#importlib.reload) will not work correctly.) If the named module does not exist in [`sys.modules`](https://docs.python.org/3/library/sys.html#sys.modules), the loader must create a new module object and add it to [`sys.modules`](https://docs.python.org/3/library/sys.html#sys.modules).
> * The module *must* exist in [`sys.modules`](https://docs.python.org/3/library/sys.html#sys.modules) before the loader executes the module code, to prevent unbounded recursion or multiple loading.
> * If loading fails, the loader must remove any modules it has inserted into [`sys.modules`](https://docs.python.org/3/library/sys.html#sys.modules), but it must remove **only** the failing module(s), and only if the loader itself has loaded the module(s) explicitly.

Changed in version 3.5: A [`DeprecationWarning`](https://docs.python.org/3/library/exceptions.html#DeprecationWarning) is raised when `exec_module()` is defined but `create_module()` is not.

Changed in version 3.6: An [`ImportError`](https://docs.python.org/3/library/exceptions.html#ImportError) is raised when `exec_module()` is defined but `create_module()` is not.

#### 5.4.2. Submodules

When a submodule is loaded using any mechanism (e.g. `importlib` APIs, the `import` or `import-from` statements, or built-in `__import__()`) a binding is placed in the parent module’s namespace to the submodule object. For example, if package `spam` has a submodule `foo`, after importing `spam.foo`, `spam` will have an attribute `foo` which is bound to the submodule. Let’s say you have the following directory structure:

```
spam/
    __init__.py
    foo.py
    bar.py
```

and `spam/__init__.py` has the following lines in it:

```
from .foo import Foo
from .bar import Bar
```

then executing the following puts a name binding to `foo` and `bar` in the `spam` module:>>>

```
>>> import spam
>>> spam.foo
<module 'spam.foo' from '/tmp/imports/spam/foo.py'>
>>> spam.bar
<module 'spam.bar' from '/tmp/imports/spam/bar.py'>
```

Given Python’s familiar name binding rules this might seem surprising, but it’s actually a fundamental feature of the import system. The invariant holding is that if you have `sys.modules['spam']` and `sys.modules['spam.foo']` (as you would after the above import), the latter must appear as the `foo` attribute of the former.

#### 5.4.3. Module spec

The import machinery uses a variety of information about each module during import, especially before loading. Most of the information is common to all modules. The purpose of a module’s spec is to encapsulate this import-related information on a per-module basis.

Using a spec during import allows state to be transferred between import system components, e.g. between the finder that creates the module spec and the loader that executes it. Most importantly, it allows the import machinery to perform the boilerplate operations of loading, whereas without a module spec the loader had that responsibility.

The module’s spec is exposed as the `__spec__` attribute on a module object. See [`ModuleSpec`](https://docs.python.org/3/library/importlib.html#importlib.machinery.ModuleSpec) for details on the contents of the module spec.

New in version 3.4.

#### 5.4.4. Import-related module attributes

The import machinery fills in these attributes on each module object during loading, based on the module’s spec, before the loader executes the module.`__name__`

The `__name__` attribute must be set to the fully-qualified name of the module. This name is used to uniquely identify the module in the import system.`__loader__`

The `__loader__` attribute must be set to the loader object that the import machinery used when loading the module. This is mostly for introspection, but can be used for additional loader-specific functionality, for example getting data associated with a loader.`__package__`

The module’s `__package__` attribute must be set. Its value must be a string, but it can be the same value as its `__name__`. When the module is a package, its `__package__` value should be set to its `__name__`. When the module is not a package, `__package__` should be set to the empty string for top-level modules, or for submodules, to the parent package’s name. See [**PEP 366**](https://www.python.org/dev/peps/pep-0366) for further details.

This attribute is used instead of `__name__` to calculate explicit relative imports for main modules, as defined in [**PEP 366**](https://www.python.org/dev/peps/pep-0366). It is expected to have the same value as `__spec__.parent`.

Changed in version 3.6: The value of `__package__` is expected to be the same as `__spec__.parent`.`__spec__`

The `__spec__` attribute must be set to the module spec that was used when importing the module. Setting `__spec__` appropriately applies equally to [modules initialized during interpreter startup](https://docs.python.org/3/reference/toplevel_components.html#programs). The one exception is `__main__`, where `__spec__` is [set to None in some cases](https://docs.python.org/3/reference/import.html#main-spec).

When `__package__` is not defined, `__spec__.parent` is used as a fallback.

New in version 3.4.

Changed in version 3.6: `__spec__.parent` is used as a fallback when `__package__` is not defined.`__path__`

If the module is a package (either regular or namespace), the module object’s `__path__` attribute must be set. The value must be iterable, but may be empty if `__path__` has no further significance. If `__path__` is not empty, it must produce strings when iterated over. More details on the semantics of `__path__` are given [below](https://docs.python.org/3/reference/import.html#package-path-rules).

Non-package modules should not have a `__path__` attribute.`__file____cached__`

`__file__` is optional. If set, this attribute’s value must be a string. The import system may opt to leave `__file__` unset if it has no semantic meaning (e.g. a module loaded from a database).

If `__file__` is set, it may also be appropriate to set the `__cached__` attribute which is the path to any compiled version of the code (e.g. byte-compiled file). The file does not need to exist to set this attribute; the path can simply point to where the compiled file would exist (see [**PEP 3147**](https://www.python.org/dev/peps/pep-3147)).

It is also appropriate to set `__cached__` when `__file__` is not set. However, that scenario is quite atypical. Ultimately, the loader is what makes use of `__file__` and/or `__cached__`. So if a loader can load from a cached module but otherwise does not load from a file, that atypical scenario may be appropriate.

#### 5.4.5. module.\_\_path\_\_

By definition, if a module has a `__path__` attribute, it is a package.

A package’s `__path__` attribute is used during imports of its subpackages. Within the import machinery, it functions much the same as [`sys.path`](https://docs.python.org/3/library/sys.html#sys.path), i.e. providing a list of locations to search for modules during import. However, `__path__` is typically much more constrained than [`sys.path`](https://docs.python.org/3/library/sys.html#sys.path).

`__path__` must be an iterable of strings, but it may be empty. The same rules used for [`sys.path`](https://docs.python.org/3/library/sys.html#sys.path) also apply to a package’s `__path__`, and [`sys.path_hooks`](https://docs.python.org/3/library/sys.html#sys.path_hooks) (described below) are consulted when traversing a package’s `__path__`.

A package’s `__init__.py` file may set or alter the package’s `__path__` attribute, and this was typically the way namespace packages were implemented prior to [**PEP 420**](https://www.python.org/dev/peps/pep-0420). With the adoption of [**PEP 420**](https://www.python.org/dev/peps/pep-0420), namespace packages no longer need to supply `__init__.py` files containing only `__path__` manipulation code; the import machinery automatically sets `__path__` correctly for the namespace package.

#### 5.4.6. Module reprs

By default, all modules have a usable repr, however depending on the attributes set above, and in the module’s spec, you can more explicitly control the repr of module objects.

If the module has a spec (`__spec__`), the import machinery will try to generate a repr from it. If that fails or there is no spec, the import system will craft a default repr using whatever information is available on the module. It will try to use the `module.__name__`, `module.__file__`, and `module.__loader__` as input into the repr, with defaults for whatever information is missing.

Here are the exact rules used:

> * If the module has a `__spec__` attribute, the information in the spec is used to generate the repr. The “name”, “loader”, “origin”, and “has\_location” attributes are consulted.
> * If the module has a `__file__` attribute, this is used as part of the module’s repr.
> * If the module has no `__file__` but does have a `__loader__` that is not `None`, then the loader’s repr is used as part of the module’s repr.
> * Otherwise, just use the module’s `__name__` in the repr.

Changed in version 3.4: Use of [`loader.module_repr()`](https://docs.python.org/3/library/importlib.html#importlib.abc.Loader.module_repr) has been deprecated and the module spec is now used by the import machinery to generate a module repr.

For backward compatibility with Python 3.3, the module repr will be generated by calling the loader’s [`module_repr()`](https://docs.python.org/3/library/importlib.html#importlib.abc.Loader.module_repr) method, if defined, before trying either approach described above. However, the method is deprecated.

#### 5.4.7. Cached bytecode invalidation

Before Python loads cached bytecode from a `.pyc` file, it checks whether the cache is up-to-date with the source `.py` file. By default, Python does this by storing the source’s last-modified timestamp and size in the cache file when writing it. At runtime, the import system then validates the cache file by checking the stored metadata in the cache file against the source’s metadata.

Python also supports “hash-based” cache files, which store a hash of the source file’s contents rather than its metadata. There are two variants of hash-based `.pyc` files: checked and unchecked. For checked hash-based `.pyc` files, Python validates the cache file by hashing the source file and comparing the resulting hash with the hash in the cache file. If a checked hash-based cache file is found to be invalid, Python regenerates it and writes a new checked hash-based cache file. For unchecked hash-based `.pyc` files, Python simply assumes the cache file is valid if it exists. Hash-based `.pyc` files validation behavior may be overridden with the [`--check-hash-based-pycs`](https://docs.python.org/3/using/cmdline.html#cmdoption-check-hash-based-pycs) flag.

Changed in version 3.7: Added hash-based `.pyc` files. Previously, Python only supported timestamp-based invalidation of bytecode caches.

### 5.5. The Path Based Finder

As mentioned previously, Python comes with several default meta path finders. One of these, called the [path based finder](https://docs.python.org/3/glossary.html#term-path-based-finder) ([`PathFinder`](https://docs.python.org/3/library/importlib.html#importlib.machinery.PathFinder)), searches an [import path](https://docs.python.org/3/glossary.html#term-import-path), which contains a list of [path entries](https://docs.python.org/3/glossary.html#term-path-entry). Each path entry names a location to search for modules.

The path based finder itself doesn’t know how to import anything. Instead, it traverses the individual path entries, associating each of them with a path entry finder that knows how to handle that particular kind of path.

The default set of path entry finders implement all the semantics for finding modules on the file system, handling special file types such as Python source code (`.py` files), Python byte code (`.pyc` files) and shared libraries (e.g. `.so` files). When supported by the [`zipimport`](https://docs.python.org/3/library/zipimport.html#module-zipimport) module in the standard library, the default path entry finders also handle loading all of these file types (other than shared libraries) from zipfiles.

Path entries need not be limited to file system locations. They can refer to URLs, database queries, or any other location that can be specified as a string.

The path based finder provides additional hooks and protocols so that you can extend and customize the types of searchable path entries. For example, if you wanted to support path entries as network URLs, you could write a hook that implements HTTP semantics to find modules on the web. This hook (a callable) would return a [path entry finder](https://docs.python.org/3/glossary.html#term-path-entry-finder) supporting the protocol described below, which was then used to get a loader for the module from the web.

A word of warning: this section and the previous both use the term *finder*, distinguishing between them by using the terms [meta path finder](https://docs.python.org/3/glossary.html#term-meta-path-finder) and [path entry finder](https://docs.python.org/3/glossary.html#term-path-entry-finder). These two types of finders are very similar, support similar protocols, and function in similar ways during the import process, but it’s important to keep in mind that they are subtly different. In particular, meta path finders operate at the beginning of the import process, as keyed off the [`sys.meta_path`](https://docs.python.org/3/library/sys.html#sys.meta_path) traversal.

By contrast, path entry finders are in a sense an implementation detail of the path based finder, and in fact, if the path based finder were to be removed from [`sys.meta_path`](https://docs.python.org/3/library/sys.html#sys.meta_path), none of the path entry finder semantics would be invoked.

#### 5.5.1. Path entry finders

The [path based finder](https://docs.python.org/3/glossary.html#term-path-based-finder) is responsible for finding and loading Python modules and packages whose location is specified with a string [path entry](https://docs.python.org/3/glossary.html#term-path-entry). Most path entries name locations in the file system, but they need not be limited to this.

As a meta path finder, the [path based finder](https://docs.python.org/3/glossary.html#term-path-based-finder) implements the [`find_spec()`](https://docs.python.org/3/library/importlib.html#importlib.abc.MetaPathFinder.find_spec) protocol previously described, however it exposes additional hooks that can be used to customize how modules are found and loaded from the [import path](https://docs.python.org/3/glossary.html#term-import-path).

Three variables are used by the [path based finder](https://docs.python.org/3/glossary.html#term-path-based-finder), [`sys.path`](https://docs.python.org/3/library/sys.html#sys.path), [`sys.path_hooks`](https://docs.python.org/3/library/sys.html#sys.path_hooks) and [`sys.path_importer_cache`](https://docs.python.org/3/library/sys.html#sys.path_importer_cache). The `__path__` attributes on package objects are also used. These provide additional ways that the import machinery can be customized.

[`sys.path`](https://docs.python.org/3/library/sys.html#sys.path) contains a list of strings providing search locations for modules and packages. It is initialized from the `PYTHONPATH` environment variable and various other installation- and implementation-specific defaults. Entries in [`sys.path`](https://docs.python.org/3/library/sys.html#sys.path) can name directories on the file system, zip files, and potentially other “locations” (see the [`site`](https://docs.python.org/3/library/site.html#module-site) module) that should be searched for modules, such as URLs, or database queries. Only strings and bytes should be present on [`sys.path`](https://docs.python.org/3/library/sys.html#sys.path); all other data types are ignored. The encoding of bytes entries is determined by the individual [path entry finders](https://docs.python.org/3/glossary.html#term-path-entry-finder).

The [path based finder](https://docs.python.org/3/glossary.html#term-path-based-finder) is a [meta path finder](https://docs.python.org/3/glossary.html#term-meta-path-finder), so the import machinery begins the [import path](https://docs.python.org/3/glossary.html#term-import-path) search by calling the path based finder’s [`find_spec()`](https://docs.python.org/3/library/importlib.html#importlib.machinery.PathFinder.find_spec) method as described previously. When the `path` argument to [`find_spec()`](https://docs.python.org/3/library/importlib.html#importlib.machinery.PathFinder.find_spec) is given, it will be a list of string paths to traverse - typically a package’s `__path__` attribute for an import within that package. If the `path` argument is `None`, this indicates a top level import and [`sys.path`](https://docs.python.org/3/library/sys.html#sys.path) is used.

The path based finder iterates over every entry in the search path, and for each of these, looks for an appropriate [path entry finder](https://docs.python.org/3/glossary.html#term-path-entry-finder) ([`PathEntryFinder`](https://docs.python.org/3/library/importlib.html#importlib.abc.PathEntryFinder)) for the path entry. Because this can be an expensive operation (e.g. there may be stat() call overheads for this search), the path based finder maintains a cache mapping path entries to path entry finders. This cache is maintained in [`sys.path_importer_cache`](https://docs.python.org/3/library/sys.html#sys.path_importer_cache) (despite the name, this cache actually stores finder objects rather than being limited to [importer](https://docs.python.org/3/glossary.html#term-importer) objects). In this way, the expensive search for a particular [path entry](https://docs.python.org/3/glossary.html#term-path-entry) location’s [path entry finder](https://docs.python.org/3/glossary.html#term-path-entry-finder) need only be done once. User code is free to remove cache entries from [`sys.path_importer_cache`](https://docs.python.org/3/library/sys.html#sys.path_importer_cache) forcing the path based finder to perform the path entry search again [3](https://docs.python.org/3/reference/import.html#fnpic).

If the path entry is not present in the cache, the path based finder iterates over every callable in [`sys.path_hooks`](https://docs.python.org/3/library/sys.html#sys.path_hooks). Each of the [path entry hooks](https://docs.python.org/3/glossary.html#term-path-entry-hook) in this list is called with a single argument, the path entry to be searched. This callable may either return a [path entry finder](https://docs.python.org/3/glossary.html#term-path-entry-finder) that can handle the path entry, or it may raise [`ImportError`](https://docs.python.org/3/library/exceptions.html#ImportError). An [`ImportError`](https://docs.python.org/3/library/exceptions.html#ImportError) is used by the path based finder to signal that the hook cannot find a [path entry finder](https://docs.python.org/3/glossary.html#term-path-entry-finder) for that [path entry](https://docs.python.org/3/glossary.html#term-path-entry). The exception is ignored and [import path](https://docs.python.org/3/glossary.html#term-import-path) iteration continues. The hook should expect either a string or bytes object; the encoding of bytes objects is up to the hook (e.g. it may be a file system encoding, UTF-8, or something else), and if the hook cannot decode the argument, it should raise [`ImportError`](https://docs.python.org/3/library/exceptions.html#ImportError).

If [`sys.path_hooks`](https://docs.python.org/3/library/sys.html#sys.path_hooks) iteration ends with no [path entry finder](https://docs.python.org/3/glossary.html#term-path-entry-finder) being returned, then the path based finder’s [`find_spec()`](https://docs.python.org/3/library/importlib.html#importlib.machinery.PathFinder.find_spec) method will store `None` in [`sys.path_importer_cache`](https://docs.python.org/3/library/sys.html#sys.path_importer_cache) (to indicate that there is no finder for this path entry) and return `None`, indicating that this [meta path finder](https://docs.python.org/3/glossary.html#term-meta-path-finder) could not find the module.

If a [path entry finder](https://docs.python.org/3/glossary.html#term-path-entry-finder) *is* returned by one of the [path entry hook](https://docs.python.org/3/glossary.html#term-path-entry-hook) callables on [`sys.path_hooks`](https://docs.python.org/3/library/sys.html#sys.path_hooks), then the following protocol is used to ask the finder for a module spec, which is then used when loading the module.

The current working directory – denoted by an empty string – is handled slightly differently from other entries on [`sys.path`](https://docs.python.org/3/library/sys.html#sys.path). First, if the current working directory is found to not exist, no value is stored in [`sys.path_importer_cache`](https://docs.python.org/3/library/sys.html#sys.path_importer_cache). Second, the value for the current working directory is looked up fresh for each module lookup. Third, the path used for [`sys.path_importer_cache`](https://docs.python.org/3/library/sys.html#sys.path_importer_cache) and returned by [`importlib.machinery.PathFinder.find_spec()`](https://docs.python.org/3/library/importlib.html#importlib.machinery.PathFinder.find_spec) will be the actual current working directory and not the empty string.

#### 5.5.2. Path entry finder protocol

In order to support imports of modules and initialized packages and also to contribute portions to namespace packages, path entry finders must implement the [`find_spec()`](https://docs.python.org/3/library/importlib.html#importlib.abc.PathEntryFinder.find_spec) method.

[`find_spec()`](https://docs.python.org/3/library/importlib.html#importlib.abc.PathEntryFinder.find_spec) takes two arguments: the fully qualified name of the module being imported, and the (optional) target module. `find_spec()` returns a fully populated spec for the module. This spec will always have “loader” set (with one exception).

To indicate to the import machinery that the spec represents a namespace [portion](https://docs.python.org/3/glossary.html#term-portion), the path entry finder sets “submodule\_search\_locations” to a list containing the portion.

Changed in version 3.4: [`find_spec()`](https://docs.python.org/3/library/importlib.html#importlib.abc.PathEntryFinder.find_spec) replaced [`find_loader()`](https://docs.python.org/3/library/importlib.html#importlib.abc.PathEntryFinder.find_loader) and [`find_module()`](https://docs.python.org/3/library/importlib.html#importlib.abc.PathEntryFinder.find_module), both of which are now deprecated, but will be used if `find_spec()` is not defined.

Older path entry finders may implement one of these two deprecated methods instead of `find_spec()`. The methods are still respected for the sake of backward compatibility. However, if `find_spec()` is implemented on the path entry finder, the legacy methods are ignored.

[`find_loader()`](https://docs.python.org/3/library/importlib.html#importlib.abc.PathEntryFinder.find_loader) takes one argument, the fully qualified name of the module being imported. `find_loader()` returns a 2-tuple where the first item is the loader and the second item is a namespace [portion](https://docs.python.org/3/glossary.html#term-portion).

For backwards compatibility with other implementations of the import protocol, many path entry finders also support the same, traditional `find_module()` method that meta path finders support. However path entry finder `find_module()` methods are never called with a `path` argument (they are expected to record the appropriate path information from the initial call to the path hook).

The `find_module()` method on path entry finders is deprecated, as it does not allow the path entry finder to contribute portions to namespace packages. If both `find_loader()` and `find_module()` exist on a path entry finder, the import system will always call `find_loader()` in preference to `find_module()`.

### 5.6. Replacing the standard import system

The most reliable mechanism for replacing the entire import system is to delete the default contents of [`sys.meta_path`](https://docs.python.org/3/library/sys.html#sys.meta_path), replacing them entirely with a custom meta path hook.

If it is acceptable to only alter the behaviour of import statements without affecting other APIs that access the import system, then replacing the builtin [`__import__()`](https://docs.python.org/3/library/functions.html#__import__) function may be sufficient. This technique may also be employed at the module level to only alter the behaviour of import statements within that module.

To selectively prevent the import of some modules from a hook early on the meta path (rather than disabling the standard import system entirely), it is sufficient to raise [`ModuleNotFoundError`](https://docs.python.org/3/library/exceptions.html#ModuleNotFoundError) directly from [`find_spec()`](https://docs.python.org/3/library/importlib.html#importlib.abc.MetaPathFinder.find_spec) instead of returning `None`. The latter indicates that the meta path search should continue, while raising an exception terminates it immediately.

### 5.7. Package Relative Imports

Relative imports use leading dots. A single leading dot indicates a relative import, starting with the current package. Two or more leading dots indicate a relative import to the parent(s) of the current package, one level per dot after the first. For example, given the following package layout:

```
package/
    __init__.py
    subpackage1/
        __init__.py
        moduleX.py
        moduleY.py
    subpackage2/
        __init__.py
        moduleZ.py
    moduleA.py
```

In either `subpackage1/moduleX.py` or `subpackage1/__init__.py`, the following are valid relative imports:

```
from .moduleY import spam
from .moduleY import spam as ham
from . import moduleY
from ..subpackage1 import moduleY
from ..subpackage2.moduleZ import eggs
from ..moduleA import foo
```

Absolute imports may use either the `import <>` or `from <> import <>` syntax, but relative imports may only use the second form; the reason for this is that:

```
import XXX.YYY.ZZZ
```

should expose `XXX.YYY.ZZZ` as a usable expression, but .moduleY is not a valid expression.

### 5.8. Special considerations for \_\_main\_\_

The [`__main__`](https://docs.python.org/3/library/__main__.html#module-__main__) module is a special case relative to Python’s import system. As noted [elsewhere](https://docs.python.org/3/reference/toplevel_components.html#programs), the `__main__` module is directly initialized at interpreter startup, much like [`sys`](https://docs.python.org/3/library/sys.html#module-sys) and [`builtins`](https://docs.python.org/3/library/builtins.html#module-builtins). However, unlike those two, it doesn’t strictly qualify as a built-in module. This is because the manner in which `__main__` is initialized depends on the flags and other options with which the interpreter is invoked.

#### 5.8.1. \_\_main\_\_.\_\_spec\_\_

Depending on how [`__main__`](https://docs.python.org/3/library/__main__.html#module-__main__) is initialized, `__main__.__spec__` gets set appropriately or to `None`.

When Python is started with the [`-m`](https://docs.python.org/3/using/cmdline.html#cmdoption-m) option, `__spec__` is set to the module spec of the corresponding module or package. `__spec__` is also populated when the `__main__` module is loaded as part of executing a directory, zipfile or other [`sys.path`](https://docs.python.org/3/library/sys.html#sys.path) entry.

In [the remaining cases](https://docs.python.org/3/using/cmdline.html#using-on-interface-options) `__main__.__spec__` is set to `None`, as the code used to populate the [`__main__`](https://docs.python.org/3/library/__main__.html#module-__main__) does not correspond directly with an importable module:

* interactive prompt
* [`-c`](https://docs.python.org/3/using/cmdline.html#cmdoption-c) option
* running from stdin
* running directly from a source or bytecode file

Note that `__main__.__spec__` is always `None` in the last case, *even if* the file could technically be imported directly as a module instead. Use the [`-m`](https://docs.python.org/3/using/cmdline.html#cmdoption-m) switch if valid module metadata is desired in [`__main__`](https://docs.python.org/3/library/__main__.html#module-__main__).

Note also that even when `__main__` corresponds with an importable module and `__main__.__spec__` is set accordingly, they’re still considered *distinct* modules. This is due to the fact that blocks guarded by `if __name__ == "__main__":` checks only execute when the module is used to populate the `__main__` namespace, and not during normal import.