lazy_import
|Build Status|
lazy_import
provides a set of functions that load modules, and related
attributes, in a lazy fashion. This allows deferring of ImportErrors
to
actual module use-time. Likewise, actual module initialization only takes place
at use-time. This is useful when using optional dependencies with heavy loading
times and/or footprints, since that cost is only paid if the module is actually
used.
For minimal impact to other code running in the same session lazy_import
functionality is implemented without the use of import hooks.
lazy_import
is compatible with Python ≥ 2.7 or ≥ 3.4.
Examples: lazy module loading
.. code:: python
import lazy_import
np = lazy_import.lazy_module("numpy")
# np is now available in the namespace and is listed in sys.modules under
# the 'numpy' key:
import sys
sys.modules['numpy']
# The module is present as "Lazily-loaded module numpy"
# Subsequent imports of the same module return the lazy version present
# in sys.modules
import numpy # At this point numpy and np point to the same lazy module.
# This is true for any import of 'numpy', even if from other modules!
# Accessing attributes causes the full loading of the module ...
np.pi
# ... and the module is changed in place. np and numpy are now
# "<module 'numpy' from '/usr/local/lib/python/site-packages/numpy/__init__.py'>"
# Lazy-importing a module that's already fully loaded returns the full
# module instead (even if it was loaded elsewhere in the current session)
# because there's no point in being lazy in this case:
os = lazy_import.lazy_module("os")
# "<module 'os' from '/usr/lib/python/os.py'>"
In the above code it can be seen that issuing
lazy_import.lazy_module("numpy")
registers the lazy module in the
session-wide sys.modules
registry. This means that any subsequent import
of numpy
in the same session, while the module is still not fully loaded,
will get served a lazy version of the numpy
module. This will happen also
outside the code that calls lazy_module
:
.. code:: python
import lazy_import
np = lazy_import.lazy_module("numpy")
import module_that_uses_numpy # This module will get a lazy module upon
# 'import numpy'
Normally this is ok because the lazy module will behave pretty much as the real
thing once fully-loaded. Still, it might be a good practice to document that
you're lazily importing modules so-and-so, so that users are warned.
Further uses are to delay ImportErrors
:
.. code:: python
import lazy_import
# The following succeeds even when asking for a module that's not available
missing = lazy_import.lazy_module("missing_module")
missing.some_attr # This causes the full loading of the module, which now fails.
"ImportError: __main__ attempted to use a functionality that requires module
missing_module, but it couldn't be loaded. Please install missing_module and retry."
Submodules work too:
.. code:: python
import lazy_import
mod = lazy_import.lazy_module("some.sub.module")
# mod now points to the some.sub.module lazy module
# equivalent to "from some.sub import module as mod"
# Alternatively the returned reference can be made to point to the
# base module:
some = lazy_import.lazy_module("some.sub.module", level="base")
# This is equivalent to "import some.sub.module" in that only the base
# module's name is added to the namespace. All submodules must be accessed
# via that:
some.sub # Returns lazy module 'some.sub' without triggering full loading.
some.sub.attr # Triggers full loading of 'some' and 'some.sub'.
some.sub.module.function() # Triggers loading also of 'some.sub.module'.
Finally, if you want to mark some modules and submodules your package imports
as always being lazy, it is as simple as lazily importing them at the root
__init__.py
level. Other files can then import all modules normally, and
those that have already been loaded as lazy in __init__.py
will remain so:
.. code:: python
# in __init__.py:
import lazy_import
lazy_import.lazy_module("numpy")
lazy_import.lazy_module("scipy.stats")
# then, in any other file in the package just use the imports normally:
import requests # This one is not lazy.
import numpy # This one is lazy, as long as no other code caused its
# loading in the meantime.
import scipy # This one is also lazy. It was lazily loaded as part of the
# lazy loading of scipy.stats.
import scipy.stats # Also lazy.
import scipy.linalg # Uh-oh, we didn't lazily import the 'linalg' submodule
# earlier, and importing it like this here will cause
# both scipy and scipy.linalg (but not scipy.stats) to
# immediately become fully loaded.
Examples: lazy callable loading
To emulate the from some.module import function
syntax lazy_module
provides lazy_callable
. It returns a wrapper function. Only upon being
called will it trigger the loading of the target module and the calling of the
target callable (function, class, etc.).
.. code:: python
import lazy_import
fn = lazy_import.lazy_callable("numpy.arange")
# 'numpy' is now in sys.modules and is 'Lazily-loaded module numpy'
fn(10)
# array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
lazy_callable
is only useful when the target callable is going to be called:
.. code:: python
import lazy_import
cl = lazy_import.lazy_callable("numpy.ndarray") # a class
obj = cl([1, 2]) # This works OK (and also triggers the loading of numpy)
class MySubclass(cl): # This fails because cl is just a wrapper,
pass # not an actual class.
Installation
.. code:: bash
pip install lazy_import
Or, to include dependencies needed to run regression tests:
.. code:: bash
pip install lazy_import[test]
Tests
The lazy_module
module comes with a series of tests. If you install with
test dependencies (see above), just run
.. code:: python
import lazy_import.test_lazy
lazy_import.test_lazy.run()
# This will automatically parallelize over the available number of cores
Alternatively, tests can be run from the command line:
.. code:: bash
pytest -n 4 --boxed -v --pyargs lazy_import
# (replace '4' with the number of cores in your machine, or set to 1 if
# you'd rather test in serial)
Tests depend only on |pytest|_ and |pytest-xdist|, so if you didn't install
them along lazy_import
(as described under Installation
) just run
.. code:: bash
pip install pytest pytest-xdist
Note that pytest-xdist
is required even for serial testing because of its
--boxed
functionality.
License
lazy_import
is released under GPL v3. It was based on code from the
|importing|_ module from the PEAK_ package. The licenses for both
lazy_import
and the PEAK package are included in the LICENSE
file. The
respective license notices are reproduced here:
lazy_import — a module to allow lazy importing of python modules
Copyright (C) 2017-2018 Manuel Nuno Melo
lazy_import is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
lazy_import is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with lazy_import. If not, see http://www.gnu.org/licenses/.
The PEAK importing
code is
Copyright (C) 1996-2004 by Phillip J. Eby and Tyler C. Sarna.
All rights reserved. This software may be used under the same terms
as Zope or Python. THERE ARE ABSOLUTELY NO WARRANTIES OF ANY KIND.
Code quality varies between modules, from "beta" to "experimental
pre-alpha". :)
Code pertaining to lazy loading from PEAK importing
was included in
lazy_import
, modified in a number of ways. These are detailed in the
CHANGELOG
file of lazy_import
. Changes mainly involved Python 3
compatibility, extension to allow customizable behavior, and added
functionality (lazy importing of callable objects).
.. |Build Status| image:: https://api.travis-ci.org/mnmelo/lazy_import.svg
:target: https://travis-ci.org/mnmelo/lazy_import
.. |importing| replace:: importing
.. |pytest| replace:: pytest
.. |pytest-xdist| replace:: pytest-xdist
.. _importing: http://peak.telecommunity.com/DevCenter/Importing
.. _PEAK: http://peak.telecommunity.com/DevCenter/FrontPage
.. _pytest: https://docs.pytest.org/en/latest/
.. _pytest-xdist: https://pypi.python.org/pypi/pytest-xdist