TLDR; Use standard-library's importlib.resources module

If you don't care for backward compatibility < Python 3.9 (explained in detailed in method no 2, below) use this:

from importlib import resources as impresources
from . import templates

inp_file = impresources.files(templates) / 'temp_file'
with inp_file.open("rt") as f:
    template = f.read()

Details

The traditional pkg_resources from setuptools is not recommended anymore because the new method:

• it is significantly more performant;
• is is safer since the use of packages (instead of path-stings) raises compile-time errors;
• it is more intuitive because you don't have to "join" paths;
• relies on Python's standard-library only (no extra 3rdp dependency setuptools).

I kept the traditional listed first, to explain the differences with the new method when porting existing code (porting also explained here).

Let's assume your templates are located in a folder nested inside your module's package:

  <your-package>
    +--<module-asking-the-file>
    +--templates/
          +--temp_file                         <-- We want this file.

Note 1: For sure, we should NOT fiddle with the __file__ attribute (e.g. code will break when served from a zip).

Note 2: If you are building this package, remember to declare your data files as package_data or data_files in your setup.py.

1) Using pkg_resources from setuptools(slow)

You may use pkg_resources package from setuptools distribution, but that comes with a cost, performance-wise:

import pkg_resources

# Could be any dot-separated package/module name or a "Requirement"
resource_package = __name__
resource_path = '/'.join(('templates', 'temp_file'))  # Do not use os.path.join()
template = pkg_resources.resource_string(resource_package, resource_path)
# or for a file-like stream:
template = pkg_resources.resource_stream(resource_package, resource_path)

Tips:

• This will read data even if your distribution is zipped, so you may set zip_safe=True in your setup.py, and/or use the long-awaited zipapp packer from python-3.5 to create self-contained distributions.

• Remember to add setuptools into your run-time requirements (e.g. in install_requires`).

... and notice that according to the Setuptools/pkg_resources docs, you should not use os.path.join:

Basic Resource Access

Note that resource names must be /-separated paths and cannot be absolute (i.e. no leading /) or contain relative names like "..". Do not use os.path routines to manipulate resource paths, as they are not filesystem paths.

2) Python >= 3.7, or using the backported importlib_resources library

Use the standard library's importlib.resources module which is more efficient than setuptools, above:

try:
    from importlib import resources as impresources
except ImportError:
    # Try backported to PY<37 `importlib_resources`.
    import importlib_resources as impresources

from . import templates  # relative-import the *package* containing the templates

try:
    inp_file = (impresources.files(templates) / 'temp_file')
    with inp_file.open("rb") as f:  # or "rt" as text file with universal newlines
        template = f.read()
except AttributeError:
    # Python < PY3.9, fall back to method deprecated in PY3.11.
    template = impresources.read_text(templates, 'temp_file')
    # or for a file-like stream:
    template = impresources.open_text(templates, 'temp_file')

Attention:

Regarding the function read_text(package, resource):

• The package can be either a string or a module.
• The resource is NOT a path anymore, but just the filename of the resource to open, within an existing package; it may not contain path separators and it may not have sub-resources (i.e. it cannot be a directory).

For the example asked in the question, we must now:

• make the <your_package>/templates/ into a proper package, by creating an empty __init__.py file in it,
• so now we can use a simple (possibly relative) import statement (no more parsing package/module names),
• and simply ask for resource_name = "temp_file" (no path).

Tips:

• To access a file inside your current module, set the package argument to __package__, e.g. impresources.read_text(__package__, 'temp_file') (thanks to @ben-mares).
• Things become interesting when an actual filename is asked with path(), since now context-managers are used for temporarily-created files (read this).
• Add the backported library, conditionally for older Pythons, with install_requires=[" importlib_resources ; python_version<'3.7'"] (check this if you package your project with setuptools<36.2.1).
• Remember to remove setuptools library from your runtime-requirements, if you migrated from the traditional method.
• Remember to customize setup.py or MANIFEST to include any static files.
• You may also set zip_safe=True in your setup.py.

A packaging prelude:

Before you can even worry about reading resource files, the first step is to make sure that the data files are getting packaged into your distribution in the first place - it is easy to read them directly from the source tree, but the important part is making sure these resource files are accessible from code within an installed package.

Structure your project like this, putting data files into a subdirectory within the package:

.                          <--- project root
├── mypackage              <--- source root
│   ├── __init__.py
│   ├── templates          <--- resources subdirectory
│   │   └── temp_file      <--- this is a data file, not code
│   ├── mymodule1.py
│   └── mymodule2.py
├── README.rst
├── MANIFEST.in
└── setup.py

You should pass include_package_data=True in the setup() call. The manifest file is only needed if you want to use setuptools/distutils and build source distributions. To make sure the templates/temp_file gets packaged for this example project structure, add a line like this into the manifest file:

recursive-include package *

Historical cruft note: Using a manifest file is not needed for modern build backends such as flit, poetry, which will include the package data files by default. So, if you're using pyproject.toml and you don't have a setup.py file then you can ignore all the stuff about MANIFEST.in.

Now, with packaging out of the way, onto the reading part...

Recommendation:

Use importlib.resources.files, it returns a traversible for accessing resources with usage similar to pathlib:

import importlib_resources

my_resources = importlib_resources.files("mypackage")
data = my_resources.joinpath("templates", "temp_file").read_bytes()

This works on Python 2 and 3, it works in zips, and it doesn't require spurious __init__.py files to be added in resource subdirectories.

Python 3.9+ is required. For older Python versions, there is a backport available to install which supports the same APIs.

Bad ways to avoid:

Bad way #1: using relative paths from a source file

This was previously described in the accepted answer. At best, it looks something like this:

from pathlib import Path

resource_path = Path(__file__).parent / "templates"
data = resource_path.joinpath("temp_file").read_bytes()

What's wrong with that? The assumption that you have files and subdirectories available is not correct. This approach doesn't work if executing code which is packed in a zip or a wheel, and it may be entirely out of the user's control whether or not your package gets extracted to a filesystem at all.

Bad way #2: using pkg_resources APIs

This is described in the top-voted answer. It looks something like this:

from pkg_resources import resource_string

data = resource_string(__name__, "templates/temp_file")

What's wrong with that? It adds a runtime dependency on setuptools, which should preferably be an install time dependency only. Importing and using pkg_resources can become really slow, as the code builds up a working set of all installed packages, even though you were only interested in your own package resources. That's not a big deal at install time (since installation is once-off), but it's ugly at runtime.

Bad way #3: using legacy importlib.resources APIs

This is currently was previously the recommendation of the top-voted answer. It's in the standard library since Python 3.7. It looks like this:

from importlib.resources import read_binary

data = read_binary("mypackage.templates", "temp_file")

What's wrong with that? Well, unfortunately, the implementation left some things to be desired and it is likely to be was deprecated in Python 3.11. Using importlib.resources.read_binary, importlib.resources.read_text and friends will require you to add an empty file templates/__init__.py so that data files reside within a sub-package rather than in a subdirectory. It will also expose the mypackage/templates subdirectory as an importable mypackage.templates sub-package in its own right. This won't work with many existing packages which are already published using resource subdirectories instead of resource sub-packages, and it's inconvenient to add the __init__.py files everywhere muddying the boundary between data and code.

This approach was deprecated in upstream importlib_resources in 2021, and was deprecated in stdlib from version Python 3.11. bpo-45514 tracked the deprecation and migrating from legacy offers _legacy.py wrappers to aid with transition.

Even more confusingly, the functional APIs may become "undeprecated" again in Python 3.13, and the names remain the same but the usage is subtly different: read_binary, read_text.

Honorable mention: using pkgutil

Long before importlib.resources existed, there was a standard library pkgutil module for accessing resources. It actually still works fine! It looks like this in library code

# within mypackage/mymodule1.py, for example
import pkgutil

data = pkgutil.get_data(__name__, "templates/temp_file")

It works in zips. It works on Python 2 and Python 3. It doesn't require any third-party dependencies. It's probably more battle-tested than importlib.resources, and might even be a better choice if you need to support a wide range of Python versions.

Example project:

I've created an example project on GitHub and uploaded on PyPI, which demonstrates all five approaches discussed above. Try it out with:

$ pip install resources-example
$ resources-example

See https://github.com/wimglenn/resources-example for more info.

The content in "10.8. Reading Datafiles Within a Package" of Python Cookbook, Third Edition by David Beazley and Brian K. Jones giving the answers.

I'll just get it to here:

Suppose you have a package with files organized as follows:

mypackage/
    __init__.py
    somedata.dat
    spam.py

Now suppose the file spam.py wants to read the contents of the file somedata.dat. To do it, use the following code:

import pkgutil
data = pkgutil.get_data(__package__, 'somedata.dat')

The resulting variable data will be a byte string containing the raw contents of the file.

The first argument to get_data() is a string containing the package name. You can either supply it directly or use a special variable, such as __package__. The second argument is the relative name of the file within the package. If necessary, you can navigate into different directories using standard Unix filename conventions as long as the final directory is still located within the package.

In this way, the package can installed as directory, .zip or .egg.

In case you have this structure

lidtk
├── bin
│   └── lidtk
├── lidtk
│   ├── analysis
│   │   ├── char_distribution.py
│   │   └── create_cm.py
│   ├── classifiers
│   │   ├── char_dist_metric_train_test.py
│   │   ├── char_features.py
│   │   ├── cld2
│   │   │   ├── cld2_preds.txt
│   │   │   └── cld2wili.py
│   │   ├── get_cld2.py
│   │   ├── text_cat
│   │   │   ├── __init__.py
│   │   │   ├── README.md   <---------- say you want to get this
│   │   │   └── textcat_ngram.py
│   │   └── tfidf_features.py
│   ├── data
│   │   ├── __init__.py
│   │   ├── create_ml_dataset.py
│   │   ├── download_documents.py
│   │   ├── language_utils.py
│   │   ├── pickle_to_txt.py
│   │   └── wili.py
│   ├── __init__.py
│   ├── get_predictions.py
│   ├── languages.csv
│   └── utils.py
├── README.md
├── setup.cfg
└── setup.py

you need this code:

import pkg_resources

# __name__ in case you're within the package
# - otherwise it would be 'lidtk' in this example as it is the package name
path = 'classifiers/text_cat/README.md'  # always use slash
filepath = pkg_resources.resource_filename(__name__, path)

The strange "always use slash" part comes from setuptools APIs

Also notice that if you use paths, you must use a forward slash (/) as the path separator, even if you are on Windows. Setuptools automatically converts slashes to appropriate platform-specific separators at build time

In case you wonder where the documentation is:

• PEP 0365
• https://packaging.python.org/guides/single-sourcing-package-version/

This is my standard way of doing it

import importlib.resources as resources
from <your_package> import __name__ as pkg_name

template_path = resources.files(pkg_name) / "template" / "temp_file"
with template_path.open() as f:
    template = f.read()

On a side note and inspired by the Maven standard dir layout I recommend the following project structure with a resources folder inside the package directory and the tests directory:

.
├── pyproject.toml
├── src
│   └── <your_package>
│       └── resources
└── tests
    └── resources

Then your temp_file would go in the resources folder and you would access the file like

template_path = resources.files(pkg_name) / "resources" / "temp_file"

The accepted answer should be to use importlib.resources. pkgutil.get_data also requires the argument package be a non-namespace package (see pkgutil docs). Hence, the directory containing the resource must have an __init__.py file, making it have the exact same limitations as importlib.resources. If the overhead issue of pkg_resources is not a concern, this is also an acceptable alternative.

Pre-Python-3.3, all packages were required to have an __init__.py. Post-Python-3.3, a folder doesn't need an __init__.py to be a package. This is called a namespace package. Unfortunately, pkgutil does not work with namespace packages (see pkgutil docs).

For example, with the package structure:

+-- foo/
|   +-- __init__.py
|   +-- bar/
|   |   +-- hi.txt

where hi.txt just has Hi!, you get the following

>>> import pkgutil
>>> rsrc = pkgutil.get_data("foo.bar", "hi.txt")
>>> print(rsrc)
None

However, with an __init__.py in bar, you get

>>> import pkgutil
>>> rsrc = pkgutil.get_data("foo.bar", "hi.txt")
>>> print(rsrc)
b'Hi!'