Deprecations#

Policy#

If the behavior of the library has to be changed, a deprecation cycle must be followed to warn users.

A deprecation cycle is not necessary when:

  • adding a new function, or

  • adding a new keyword argument to the end of a function signature, or

  • fixing buggy behavior

A deprecation cycle is necessary for any breaking API change, meaning a change where the function, invoked with the same arguments, would return a different result after the change. This includes:

  • changing the order of arguments or keyword arguments, or

  • adding arguments or keyword arguments to a function, or

  • changing the name of a function, class, method, etc., or

  • moving a function, class, etc. to a different module, or

  • changing the default value of a function’s arguments.

Usually, our policy is to put in place a deprecation cycle over two minor releases (e.g., if a deprecation warning appears in 2.3, then the functionality should be removed in 2.5). For major releases we usually require that all deprecations have at least a 1-release deprecation cycle (e.g., if 3.0 occurs after 2.5, then all removed functionality in 3.0 should be deprecated in 2.5).

Note that these 1- and 2-release deprecation cycles for major and minor releases is not a strict rule and in some cases, the developers can agree on a different procedure upon justification (like when we can’t detect the change, or it involves moving or deleting an entire function for example).

Procedure#

To set up a function for deprecation:

  • Use a deprecation warning to warn users. For example:

    msg = "curly_hair is deprecated and will be removed in v3.0. Use sum() instead."
warnings.warn(msg, DeprecationWarning)

  • Add a warnings filter to networkx/conftest.py:

    warnings.filterwarnings(
    "ignore", category=DeprecationWarning, message=<start of message>
)

  • Add a reminder to doc/developer/deprecations.rst for the team to remove the deprecated functionality in the future. For example:

    * In ``utils/misc.py`` remove ``generate_unique_node`` and related tests.

Note

To reviewers: make sure the merge message has a brief description of the change(s) and if the PR closes an issue add, for example, “Closes #123” where 123 is the issue number.

Todo#

Make sure to review networkx/conftest.py after removing deprecated code.

Version 3.7#

  • Remove graph_could_be_isomorphic, fast_graph_could_be_isomorphic, and faster_graph_could_be_isomorphic, from networkx.algorithms.isomorphism.isomorph.

  • Remove random_lobster from networkx.generators.random_graphs.

Version 3.8#

  • Remove maybe_regular_expander from networkx.generators.expanders.

  • In algorithms/approximation/steinertree.py remove metric_closure and related tests.