5. The import system¶
Python code in one module gains access to the code in another module
by the process of importing it. The
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() and built-in
__import__() can also be used to invoke the import machinery.
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__() function, with the appropriate arguments.
The return value of
__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
A direct call to
__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
sys.modules), only the
import statement performs
a name binding operation.
import statement is executed, the standard builtin
__import__() function is called. Other mechanisms for invoking the
import system (such as
importlib.import_module()) may choose to bypass
__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, initializing it. If the named module
cannot be found, a
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. There is no longer any implicit import machinery - the full
import system is exposed through
sys.meta_path. In addition,
native namespace package support has been implemented (see PEP 420).
importlib module provides a rich API for interacting with the
import system. For example
importlib.import_module() provides a
recommended, simpler API than built-in
__import__() for invoking the
import machinery. Refer to the
importlib library documentation for
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.
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 package called
email.mime and a module within that subpackage called
5.2.1. Regular packages¶
Python defines two types of packages, regular packages and namespace packages. 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
package with three subpackages:
parent/ __init__.py one/ __init__.py two/ __init__.py three/ __init__.py
parent.one will implicitly execute
parent/one/__init__.py. Subsequent imports of
parent.three will execute
5.2.2. Namespace packages¶
A namespace package is a composite of various portions, 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
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 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 for the namespace package specification.
To begin the search, Python needs the fully qualified
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 statement, or from the parameters to the
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.bar, and finally
If any of the intermediate imports fail, a
ModuleNotFoundError is raised.
5.3.1. The module cache¶
The first place checked during import search is
mapping serves as a cache of all modules that have been previously imported,
including the intermediate paths. So if
foo.bar.baz was previously
sys.modules will contain entries for
foo.bar.baz. Each key will have as its value the corresponding module
During import, the module name is looked up in
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 is raised. If the module name is missing, Python will
continue searching for the module.
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
Beware though, as if you keep a reference to the module object,
invalidate its cache entry in
sys.modules, and then re-import the
named module, the two module objects will not be the same. By contrast,
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, then Python’s import
protocol is invoked to find and load the module. This protocol consists of
two conceptual objects, finders and loaders.
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 - 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 for modules. The 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 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 cache look up.
This allows meta hooks to override
sys.path processing, frozen
modules, or even built-in modules. Meta hooks are registered by adding new
finder objects to
sys.meta_path, as described below.
Import path hooks are called as part of
package.__path__) processing, at the point where their associated path
item is encountered. Import path hooks are registered by adding new callables
sys.path_hooks as described below.
5.3.4. The meta path¶
When the named module is not found in
sys.modules, Python next
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() 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
sys.meta_path processing reaches the end of its list without returning
a spec, then a
ModuleNotFoundError is raised. Any other exceptions
raised are simply propagated up, aborting the import process.
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
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 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,
foo.bar.baz will first perform a top level import, calling
mpf.find_spec("foo", None, None) on each meta path finder (
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
None when anything other than
None is passed as the
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
(i.e. the path based finder).
Changed in version 3.4: The
find_spec() method of meta path
is now deprecated. While it will continue to work without change, the
import machinery will try it only if the finder does not implement
Changed in version 3.10: Use of
find_module() by the import system
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, import will have already returned it.
The module will exist in
sys.modulesbefore the loader executes the module code. This is crucial because the module code may (directly or indirectly) import itself; adding it to
sys.modulesbeforehand 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. Any module already in the
sys.modulescache, 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
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.
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.
Changed in version 3.4: The import system has taken over the boilerplate responsibilities of
loaders. These were previously performed by the
Module loaders provide the critical function of loading: module execution.
The import machinery calls the
method with a single argument, the module object to execute. Any value
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 (
If the loader cannot execute the module, it should raise an
ImportError, although any other exception raised during
exec_module()will be propagated.
In many cases, the finder and loader can be the same object; in such cases the
find_spec() method would just return a
spec with the loader set to
Module loaders may opt in to creating the module object during loading
by implementing a
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
import machinery will create the new module itself.
New in version 3.4: The
create_module() method of loaders.
Changed in version 3.4: The
load_module() method was replaced by
exec_module() and the import
machinery assumed all the boilerplate responsibilities of loading.
For compatibility with existing loaders, the import machinery will use
load_module() method of loaders if it exists and the loader does
not also implement
load_module() has been
deprecated and loaders should implement
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, the loader must use that existing module. (Otherwise,
importlib.reload()will not work correctly.) If the named module does not exist in
sys.modules, the loader must create a new module object and add it to
The module must exist in
sys.modulesbefore 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, 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 is raised when
exec_module() is defined but
create_module() is not.
Changed in version 3.6: An
ImportError is raised when
exec_module() is defined but
create_module() is not.
Changed in version 3.10: Use of
load_module() will raise
When a submodule is loaded using any mechanism (e.g.
importlib APIs, the
import-from statements, or built-in
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 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
spam/__init__.py has the following line in it:
from .foo import Foo
then executing the following puts name bindings for
Foo in the
>>> import spam >>> spam.foo <module 'spam.foo' from '/tmp/imports/spam/foo.py'> >>> spam.Foo <class 'spam.foo.Foo'>
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.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.
ModuleSpec for details on the contents of
the module spec.
New in version 3.4.
By definition, if a module has a
__path__ attribute, it is a package.
__path__ attribute is used during imports of its subpackages.
Within the import machinery, it functions much the same as
i.e. providing a list of locations to search for modules during import.
__path__ is typically much more constrained than
__path__ must be an iterable of strings, but it may be empty.
The same rules used for
sys.path also apply to a package’s
sys.path_hooks (described below) are
consulted when traversing a package’s
__init__.py file may set or alter the package’s
attribute, and this was typically the way namespace packages were implemented
prior to PEP 420. With the adoption of PEP 420, namespace packages no
longer need to supply
__init__.py files containing only
manipulation code; the import machinery automatically sets
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.__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
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() method, if defined, before
trying either approach described above. However, the method is deprecated.
Changed in version 3.10: Calling
module_repr() now occurs after trying to
use a module’s
__spec__ attribute but before falling back on
__file__. Use of
module_repr() is slated to
stop in Python 3.12.
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
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
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
validation behavior may be overridden with the
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
PathFinder), searches an import path,
which contains a list of path entries. 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
.py files), Python byte code (
.pyc files) and
shared libraries (e.g.
.so files). When supported by the
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 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 and
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
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
sys.meta_path, none of the path entry finder semantics
would be invoked.
5.5.1. Path entry finders¶
The path based finder is responsible for finding and loading Python modules and packages whose location is specified with a string 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 implements the
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.
Three variables are used by the path based finder,
attributes on package objects are also used. These provide additional ways
that the import machinery can be customized.
sys.path contains a list of strings providing search locations for
modules and packages. It is initialized from the
environment variable and various other installation- and
implementation-specific defaults. Entries in
sys.path can name
directories on the file system, zip files, and potentially other “locations”
site module) that should be searched for modules, such as
URLs, or database queries. Only strings should be present on
sys.path; all other data types are ignored.
The path based finder is a meta path finder, so the import
machinery begins the import path search by calling the path
find_spec() method as
described previously. When the
path argument to
find_spec() is given, it will be a
list of string paths to traverse - typically a package’s
attribute for an import within that package. If the
path argument is
None, this indicates a top level import and
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
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
sys.path_importer_cache (despite the name, this cache actually
stores finder objects rather than being limited to importer objects).
In this way, the expensive search for a particular path entry
location’s path entry finder need only be done once. User code is
free to remove cache entries from
the path based finder to perform the path entry search again 3.
If the path entry is not present in the cache, the path based finder iterates
over every callable in
sys.path_hooks. Each of the path entry
hooks in this list is called with a single argument, the
path entry to be searched. This callable may either return a path
entry finder that can handle the path entry, or it may raise
ImportError is used by the path based finder to
signal that the hook cannot find a path entry finder
for that path entry. The
exception is ignored and 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
sys.path_hooks iteration ends with no path entry finder
being returned, then the path based finder’s
find_spec() method will store
sys.path_importer_cache (to indicate that there is no finder for
this path entry) and return
None, indicating that this
meta path finder could not find the module.
If a path entry finder is returned by one of the path entry
hook callables on
sys.path_hooks, then the following protocol is used
to ask the finder for a module spec, which is then used when loading the
The current working directory – denoted by an empty string – is handled
slightly differently from other entries on
sys.path. First, if the
current working directory is found to not exist, no value is stored in
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 and returned by
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
find_spec() takes two arguments: the
fully qualified name of the module being imported, and the (optional) target
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, the path entry finder sets “submodule_search_locations” to a list containing the portion.
Changed in version 3.4:
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
find_spec(). The methods are still respected for the
sake of backward compatibility. However, if
implemented on the path entry finder, the legacy methods are ignored.
find_loader() takes one argument, the
fully qualified name of the module being imported.
returns a 2-tuple where the first item is the loader and the second item
is a namespace portion.
For backwards compatibility with other implementations of the import
protocol, many path entry finders also support the same,
find_module() method that meta path finders support.
However path entry finder
find_module() methods are never called
path argument (they are expected to record the appropriate
path information from the initial call to the path hook).
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
exist on a path entry finder, the import system will always call
find_loader() in preference to
Changed in version 3.10: Calls to
find_loader() by the import
system will raise
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, 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
__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 directly from
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
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:
XXX.YYY.ZZZ as a usable expression, but .moduleY is
not a valid expression.
5.8. Special considerations for __main__¶
__main__ module is a special case relative to Python’s import
system. As noted elsewhere, the
is directly initialized at interpreter startup, much like
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.
Depending on how
__main__ is initialized,
gets set appropriately or to
When Python is started with the
__spec__ is set
to the module spec of the corresponding module or package.
also populated when the
__main__ module is loaded as part of executing a
directory, zipfile or other
In the remaining cases
__main__.__spec__ is set to
None, as the code used to populate the
__main__ does not correspond directly with an importable module:
running from stdin
running directly from a source or bytecode file
__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 switch if valid module metadata is desired
Note also that even when
__main__ corresponds with an importable module
__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.
The import machinery has evolved considerably since Python’s early days. The original specification for packages is still available to read, although some details have changed since the writing of that document.
The original specification for
sys.meta_path was PEP 302, with
subsequent extension in PEP 420.
PEP 420 introduced namespace packages for
Python 3.3. PEP 420 also introduced the
find_loader() protocol as an
PEP 366 describes the addition of the
__package__ attribute for
explicit relative imports in main modules.
PEP 328 introduced absolute and explicit relative imports and initially
__name__ for semantics PEP 366 would eventually specify for
PEP 338 defines executing modules as scripts.
PEP 451 adds the encapsulation of per-module import state in spec objects. It also off-loads most of the boilerplate responsibilities of loaders back onto the import machinery. These changes allow the deprecation of several APIs in the import system and also addition of new methods to finders and loaders.
The importlib implementation avoids using the return value directly. Instead, it gets the module object by looking the module name up in
sys.modules. The indirect effect of this is that an imported module may replace itself in
sys.modules. This is implementation-specific behavior that is not guaranteed to work in other Python implementations.
In legacy code, it is possible to find instances of
sys.path_importer_cache. It is recommended that code be changed to use
Noneinstead. See Porting Python code for more details.