Using importlib_resources

importlib_resources is a library that leverages Python’s import system to provide access to resources within packages. Given that this library is built on top of the import system, it is highly efficient and easy to use. This library’s philosophy is that, if you can import a package, you can access resources within that package. Resources can be opened or read, in either binary or text mode.

What exactly do we mean by “a resource”? It’s easiest to think about the metaphor of files and directories on the file system, though it’s important to keep in mind that this is just a metaphor. Resources and packages do not have to exist as physical files and directories on the file system.

If you have a file system layout such as:


then the directories are data, data/one, and data/two. Each of these are also Python packages by virtue of the fact that they all contain files. That means that in Python, all of these import statements work:

import data
from data import two

Each import statement gives you a Python module corresponding to the file in each of the respective directories. These modules are packages since packages are just special module instances that have an additional attribute, namely a __path__ [1].

In this analogy then, resources are just files or directories contained in a package directory, so data/one/resource1.txt and data/two/resource2.txt are both resources, as are the files in all the directories.

Resources are always accessed relative to the package that they live in. resource1.txt and resources1/resource1.1.txt are resources within the package, and two/resource2.txt is a resource within the data package.


Let’s say you are writing an email parsing library and in your test suite you have a sample email message in a file called message.eml. You would like to access the contents of this file for your tests, so you put this in your project under the email/tests/data/message.eml path. Let’s say your unit tests live in email/tests/

Your test could read the data file by doing something like:

data_dir = os.path.join(os.path.dirname(__file__), 'tests', 'data')
data_path = os.path.join(data_dir, 'message.eml')
with open(data_path, encoding='utf-8') as fp:
    eml =

But there’s a problem with this! The use of __file__ doesn’t work if your package lives inside a zip file, since in that case this code does not live on the file system.

You could use the pkg_resources API like so:

# In Python 3, resource_string() actually returns bytes!
from pkg_resources import resource_string as resource_bytes
eml = resource_bytes('', 'message.eml').decode('utf-8')

This requires you to make Python packages of both email/tests and email/tests/data, by placing an empty files in each of those directories.

The problem with the pkg_resources approach is that, depending on the packages in your environment, pkg_resources can be expensive just to import. This behavior can have a serious negative impact on things like command line startup time for Python implement commands.

importlib_resources solves this performance challenge by being built entirely on the back of the stdlib importlib. By taking advantage of all the efficiencies in Python’s import system, and the fact that it’s built into Python, using importlib_resources can be much more performant. The equivalent code using importlib_resources would look like:

from importlib_resources import files
# Reads contents with UTF-8 encoding and returns str.
eml = files('').joinpath('message.eml').read_text()

Packages or package names

All of the importlib_resources APIs take a package as their first parameter, but this can either be a package name (as a str) or an actual module object, though the module must be a package. If a string is passed in, it must name an importable Python package, and this is first imported. Thus the above example could also be written as:

eml = files('message.eml').read_text()

File system or zip file

In general you never have to worry whether your package is on the file system or in a zip file, as the importlib_resources APIs hide those details from you. Sometimes though, you need a path to an actual file on the file system. For example, some SSL APIs require a certificate file to be specified by a real file system path, and C’s dlopen() function also requires a real file system path.

To support this, importlib_resources provides an API that will extract the resource from a zip file to a temporary file, and return the file system path to this temporary file as a pathlib.Path object. In order to properly clean up this temporary file, what’s actually returned is a context manager that you can use in a with-statement:

from importlib_resources import files, as_file

source = files('message.eml')
with as_file(source) as eml:

You can use all the standard contextlib APIs to manage this context manager.


There is an odd interaction with Python 3.4, 3.5, and 3.6 regarding adding zip or wheel file paths to sys.path. Due to limitations in zipimport, which can’t be changed without breaking backward compatibility, you must use an absolute path to the zip/wheel file. If you use a relative path, you will not be able to find resources inside these zip files. E.g.:


files('foo')  # This will fail!



Both relative and absolute paths work for Python 3.7 and newer.

Migrating from Legacy

Starting with Python 3.9 and importlib_resources 1.4, this package introduced the files() API, to be preferred over the legacy API, i.e. the functions open_binary, open_text, path, contents, read_text, read_binary, and is_resource.

To port to the files() API, refer to the _legacy module to see simple wrappers that enable drop-in replacement based on the preferred API, and either copy those or adapt the usage to utilize the files and Traversable interfaces directly.


Starting with Python 3.9 and importlib_resources 2.0, this package provides an interface for non-standard loaders, such as those used by executable bundlers, to supply resources. These loaders should supply a get_resource_reader method, which is passed a module name and should return a TraversableResources instance.