Starting from the 1.0.0 release, Qiskit follows semantic versioning, with a yearly release cycle for major releases. Full details of the scheduling are hosted with the external public documentation.
This document is primarily intended for developers of Qiskit themselves.
Many users and other packages depend on different parts of Qiskit. We must make sure that whenever we make changes to the code, we give users ample time to adjust without breaking code that they have already written.
Most importantly: do not change any interface that is public-facing unless we absolutely have to. Adding things is ok, taking things away is annoying for users but can be handled reasonably with plenty notice, but changing behavior generally means users cannot write code that will work with two subsequent versions of Qiskit, which is not acceptable.
Beware that users will often be using functions, classes and methods that we,
the Qiskit developers, may consider internal or not widely used. Do not make
assumptions that "this is buried, so nobody will be using it"; if it is public,
it is subject to the policy. The only exceptions here are functions and modules
that are explicitly internal, i.e. those whose names begin with a leading
underscore (_
).
The guiding principles are:
-
removals or behavior changes in the public API can only occur in major releases;
-
new deprecations to the public API can only occur in minor releases;
-
there must always be a way to achieve valid goals that does not issue any warnings with the most recent two minor releases in a series;
-
never assume that an object that is part of the public interface is not in use.
While the no-breaking-changes rule is only formally required within a major release series, you should make every effort to avoid breaking changes wherever possible. Similarly, while it is permissible where necessary for behavior to change with no single-code path to support both the last minor of one major release and the first minor of a new major release, it is still strongly preferable if you can achieve this.
Note
This section should be in sync with the release schedule documentation of Qiskit. Please open an issue against Qiskit if there are discrepancies so we can clarify them.
For the purposes of semantic versioning, the Qiskit public API comprises all publicly documented packages, modules, classes, functions, methods, and attributes.
An object is publicly documented if and only if it appears in the hosted API documentation for Qiskit.
The presence of a docstring in the Python source (or a __doc__
attribute) is not sufficient to make an object publicly documented; this documentation must also be rendered in the public API documentation.
As well as the objects themselves needing to be publicly documented, the only public-API import locations for a given object is the location it is documented at in the public API documentation, and parent modules or packages that re-export the object (if any).
For example, while it is possible to import Measure
from qiskit.circuit.measure
, this is not a supported part of the public API for two reasons:
- The module
qiskit.circuit.measure
is not publicly documented, so is not part of the public interface. - The
Measure
object is documented as being inqiskit.circuit.library
, and is re-exported byqiskit.circuit
, so the public import paths arefrom qiskit.circuit.library import Measure
andfrom qiskit.circuit import Measure
.
As a rule of thumb, if you are using Qiskit, you should import objects from the highest-level package that exports that object.
Some components of the documented public interface may be marked as "experimental", and not subject to the stability guarantees of semantic versioning.
These will be clearly denoted in the documentation, and will raise an ExperimentalWarning
when used.
We will only use these "experimental" features sparingly, when we feel there is a real benefit to making the experimental version public in an unstable form, such as a backwards-incompatible new version of core functionality that shows significant improvements over the existing form for limited inputs, but is not yet fully feature complete.
Typically, a feature will only become part of the public API when we are ready to commit to its stability properly.
Important
Features can only be removed in new major versions. Deprecations can only be added in new minor versions.
When removing a feature (for example a class, function or function parameter), we will follow this procedure:
-
The alternative path must be in place for one minor version before any warnings are issued. For example, if we want to replace the function
foo()
withbar()
, we must make at least one minor release with both functions before issuing any warnings withinfoo()
. You may issuePendingDeprecationWarning
s from the old paths immediately, but this is not necessary and does not affect any timelines for removal.Reason: we need to give people time to swap over without breaking their code as soon as they upgrade.
-
After the alternative path has been in place for at least one minor version, issue the deprecation warnings. Add a release note with a
deprecations
section listing all deprecated paths, their alternatives, and the reason for deprecation. Update the tests to test the warnings.Reason: removals must be highly visible for at least one version, to minimize the surprise to users when they actually go.
-
Apply the removal to the branch for the next major release, or open an issue to remind us to effect the removal and tag it for the milestone of the next major release.
Note
These are minimum requirements. For removal of significant or core features, try to give as long a warning period as is feasible.
When a feature is marked as deprecated it is slated for removal, but users should still be able to rely on it to work correctly. We consider a feature marked "deprecated" as frozen; we commit to maintaining it with critical bug fixes until it is removed, but we won't merge new functionality to it.
Important
Breaking behavior changes can only occur in new major versions, and should be avoided as much as possible.
Changing behavior without a removal is particularly difficult to manage, because we need to have both options available for two versions, and be able to issue warnings. For example, changing the type of the return value from a function will almost invariably involve making an API break, which is frustrating for users and makes it difficult for them to use Qiskit.
The best solution here is often to make a new function, and then use the procedures for removal above.
If you absolutely must change the behavior of existing code (other than fixing
bugs), you will need to use your best judgment to apply the guiding principles
at the top of this document. The most appropriate warning for behavioral
changes is usually FutureWarning
. Some possibilities for how to effect a
change:
-
If you are changing the default behavior of a function, consider adding a keyword argument to select between old and new behaviors. When it comes time, you can issue a
FutureWarning
if the keyword argument is not given (e.g. if it isNone
), saying that the new value will soon become the default. You will need to go through the normal deprecation period for removing this keyword argument after you have made the behavior change. This will take at least six months to go through both cycles. -
If you need to change the return type of a function, consider adding a new function that returns the new type, and then follow the procedures for deprecating the old function.
-
If you need to accept a new input that you cannot distinguish from an existing possibility because of its type, consider letting it be passed by a different keyword argument, or add a second function that only accepts the new form.
The proper way to raise a deprecation warning is to use the decorators @deprecate_arg
and
@deprecate_func
from qiskit.utils.deprecation
. These will generate a standardized message and
and add the deprecation to that function's docstring so that it shows up in the docs.
from qiskit.utils.deprecation import deprecate_arg, deprecate_func
@deprecate_func(since="0.24.0", additional_msg="No replacement is provided.")
def deprecated_func():
pass
@deprecate_arg("bad_arg", new_alias="new_name", since="0.24.0")
def another_func(bad_arg: str, new_name: str):
pass
Usually, you should set additional_msg: str
with the format "Instead, use ..."
so that
people know how to migrate. Read those functions' docstrings for additional arguments like
pending: bool
and predicate
.
If you are deprecating outside the main Qiskit repo, set package_name
to match your package.
Alternatively, if you prefer to use your own decorator helpers, then have them call
add_deprecation_to_docstring
from qiskit.utils.deprecation
.
If @deprecate_func
and @deprecate_arg
cannot handle your use case, consider improving
them. Otherwise, you can directly call the warn
function
from the warnings module in the Python standard library,
using the category DeprecationWarning
. For example:
import warnings
def deprecated_function():
warnings.warn(
"The function qiskit.deprecated_function() is deprecated since "
"Qiskit 0.44.0, and will be removed 3 months or more later. "
"Instead, you should use qiskit.other_function().",
category=DeprecationWarning,
stacklevel=2,
)
# ... the rest of the function ...
Make sure you include the version of the package that introduced the deprecation warning (so maintainers can easily see when it is valid to remove it), and what the alternative path is.
Take note of the stacklevel
argument. This controls which function is
accused of being deprecated. Setting stacklevel=1
(the default) means the
warning will blame the warn
function itself, while stacklevel=2
will
correctly blame the containing function. It is unusual to set this to anything
other than 2
, but can be useful if you use a helper function to issue the
same warning in multiple places.
Whenever you add deprecation warnings, you will need to update tests involving the functionality. The test suite should fail otherwise, because of the new warnings. We must continue to test deprecated functionality throughout the deprecation period, to ensure that it still works.
To update the tests, you need to wrap each call of deprecated behavior in its
own assertion block. For subclasses of unittest.TestCase
(which all Qiskit
test cases are), this is done by:
class MyTestSuite(QiskitTestCase):
def test_deprecated_function(self):
with self.assertWarns(DeprecationWarning):
output = deprecated_function()
# ... do some things with output ...
self.assertEqual(output, expected)
It is important to warn the user when your breaking changes are coming.
@deprecate_arg
and @deprecate_func
will automatically add the deprecation to the docstring
for the function so that it shows up in docs.
If you are not using those decorators, you should directly add a Sphinx deprecated directive:
def deprecated_function():
"""
Short description of the deprecated function.
.. deprecated:: 0.44.0
The function qiskit.deprecated_function() is deprecated since
Qiskit 0.44.0, and will be removed 3 months or more later.
Instead, you should use qiskit.other_function().
<rest of the docstring>
"""
# ... the rest of the function ...
You should also document the deprecation in the changelog by using Reno. Explain the deprecation and how to migrate.
In particular situations where a deprecation or change might be a major disruptor for users, a
migration guide might be needed. Please write these guides in Qiskit's documentation at
https://github.com/Qiskit/documentation/tree/main/docs/api/migration-guides. Once
the migration guide is written and published, deprecation
messages and documentation should link to it (use the additional_msg
argument for
@deprecate_arg
and @deprecate_func
).