# 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.

The `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 operation.

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 (including `sys.modules`), only the `import` statement performs a name binding operation.

When an `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).

## 5.1. `importlib`

The `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 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.

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`, which in turn has a subpackage called `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 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 `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.

A subdirectory inside a regular package that does not contain an `__init__.py` file is treated as an implicit namespace package (a “namespace subpackage”) rooted in that parent. See PEP 420 for the underlying specification.

### 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 `__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` 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.

Namespace packages may also be nested inside a regular package. When the import system searches a regular package’s `__path__` and encounters a subdirectory that does not contain an `__init__.py` file, that subdirectory becomes a portion contributing to a namespace subpackage of the enclosing regular package.

See also PEP 420 for the namespace package specification.

## 5.3. Searching

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 `importlib.import_module()` or `__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` is raised.

### 5.3.1. The module cache

The first place checked during import search is `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` 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` 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 `ModuleNotFoundError`.

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 `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` as described below.

### 5.3.4. The meta path

When the named module is not found in `sys.modules`, Python next searches `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 `None`. If `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.

The `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` 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` 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 finders replaced `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()`.

Changed in version 3.10: Use of `find_module()` by the import system now raises `ImportWarning`.

Changed in version 3.12: `find_module()` has been removed. Use `find_spec()` instead.

## 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

    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.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` 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`. Any module already in the `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`.

- 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 `importlib.abc.Loader.load_module` method.

Changed in version 3.15: The `load_module` method is no longer used.

### 5.4.1. Loaders

Module loaders provide the critical function of loading: module execution. The import machinery calls the `importlib.abc.Loader.exec_module()` method with a single argument, the module object to execute. Any value returned from `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`, 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 `self`.

Module loaders may opt in to creating the module object during loading by implementing a `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.

Added in version 3.4: The `create_module()` method of loaders.

Changed in version 3.4: The `importlib.abc.Loader.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 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`, 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 `sys.modules`.

- The module must exist in `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`, 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 `ImportWarning`.

### 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

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

    from .foo import Foo

then executing the following puts name bindings for `foo` and `Foo` in the `spam` module:

    >>> 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']` 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 specs

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 `module.__spec__`. Setting `__spec__` appropriately applies equally to modules initialized during interpreter startup. The one exception is `__main__`, where `__spec__` is set to None in some cases.

See `ModuleSpec` for details on the contents of the module spec.

Added in version 3.4.

### 5.4.4. __path__ attributes on modules

The `__path__` attribute should be a (possibly empty) sequence of strings enumerating the locations where the package’s submodules will be found. 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`, i.e. providing a list of locations to search for modules during import. However, `__path__` is typically much more constrained than `sys.path`.

The same rules used for `sys.path` also apply to a package’s `__path__`. `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. With the adoption of PEP 420, 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.

### 5.4.5. 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 3.12: Use of `module_repr()`, having been deprecated since Python 3.4, was removed in Python 3.12 and is no longer called during the resolution of a module’s repr.

### 5.4.6. 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` 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 (`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 code (`.py` files), Python byte code (`.pyc` files) and shared libraries (e.g. `.so` files). When supported by the `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 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 `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`, 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, `sys.path`, `sys.path_hooks` and `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` 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` can name directories on the file system, zip files, and potentially other “locations” (see the `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 based finder’s `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 `__path__` 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 in `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 `sys.path_importer_cache` forcing the path based finder to perform the path entry search again.

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`. An `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 `ImportError`.

If `sys.path_hooks` iteration ends with no path entry finder being returned, then the path based finder’s `find_spec()` method will store `None` in `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 module.

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 cannot be determined or is found not to 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 the `find_spec()` method.

`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, the path entry finder sets `submodule_search_locations` to a list containing the portion.

Changed in version 3.4: `find_spec()` replaced `find_loader()` and `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()` 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.

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()`.

Changed in version 3.10: Calls to `find_module()` and `find_loader()` by the import system will raise `ImportWarning`.

Changed in version 3.12: `find_module()` and `find_loader()` have been removed.

## 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 the builtin `__import__()` function may be sufficient.

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

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__` module is a special case relative to Python’s import system. As noted elsewhere, the `__main__` module is directly initialized at interpreter startup, much like `sys` and `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__` is initialized, `__main__.__spec__` gets set appropriately or to `None`.

When Python is started with the `-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` entry.

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:

- interactive prompt

- `-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` switch if valid module metadata is desired in `__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.

## 5.9. References

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 alternative to `find_module()`.

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 proposed `__name__` for semantics PEP 366 would eventually specify for `__package__`.

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.

Footnotes

[1]

See `types.ModuleType`.

[2]

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.