chore(deps): update github/codeql-action action to v4.31.7

[renovate]

This PR contains the following updates:

Package	Type	Update	Change
github/codeql-action	action	patch	v4.31.0 -> v4.31.7

---

Release Notes

github/codeql-action (github/codeql-action)

v4.31.7

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CodeQL Action Changelog

See the releases page for the relevant changes to the CodeQL CLI and language packs.

4.31.7 - 05 Dec 2025

• Update default CodeQL bundle version to 2.23.7. #​3343

See the full CHANGELOG.md for more information.

v4.31.6

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CodeQL Action Changelog

See the releases page for the relevant changes to the CodeQL CLI and language packs.

4.31.6 - 01 Dec 2025

No user facing changes.

See the full CHANGELOG.md for more information.

v4.31.5

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CodeQL Action Changelog

See the releases page for the relevant changes to the CodeQL CLI and language packs.

4.31.5 - 24 Nov 2025

• Update default CodeQL bundle version to 2.23.6. #​3321

See the full CHANGELOG.md for more information.

v4.31.4

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CodeQL Action Changelog

See the releases page for the relevant changes to the CodeQL CLI and language packs.

4.31.4 - 18 Nov 2025

No user facing changes.

See the full CHANGELOG.md for more information.

v4.31.3

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CodeQL Action Changelog

See the releases page for the relevant changes to the CodeQL CLI and language packs.

4.31.3 - 13 Nov 2025

• CodeQL Action v3 will be deprecated in December 2026. The Action now logs a warning for customers who are running v3 but could be running v4. For more information, see Upcoming deprecation of CodeQL Action v3.
• Update default CodeQL bundle version to 2.23.5. #​3288

See the full CHANGELOG.md for more information.

v4.31.2

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v4.31.1

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[codecov]

❌ 1 Tests Failed:

Tests completed	Failed	Passed	Skipped
105	1	104	16

View the top 1 failed test(s) by shortest run time

tests\test_ruleset.py::test_ruleset::test_solve_total_value[HIGHS]

Stack Traces | 0.07s run time

ruleset = RuleSet(numbers=13, repeats=2, colours=4, jokers=2, min_len=3, min_initial_value=30, solver_backend=<MILPSolver.HIGHS: 'HIGHS'>)
in_progress_game = <GameState([... 53 tiles ...], table=(<Black 1 (1)>, <Black 2 (2)>, <Black 3 (3)>, <Black 4 (4)>, <Black 5 (5)>, <Blac... 9 (35)>, <Orange 12 (38)>, <Orange 12 (38)>, <Red 2 (41)>, <Red 4 (43)>, <Red 7 (46)>, <Red 12 (51)>), initial=False)>

    #x1B[0m#x1B[94mdef#x1B[39;49;00m#x1B[90m #x1B[39;49;00m#x1B[92mtest_solve_total_value#x1B[39;49;00m(ruleset: RuleSet, in_progress_game: GameState) -> #x1B[94mNone#x1B[39;49;00m:#x1B[90m#x1B[39;49;00m
        in_progress_game.initial = #x1B[94mFalse#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        solution = ruleset.solve(in_progress_game, mode=SolverMode.TOTAL_VALUE)#x1B[90m#x1B[39;49;00m
        #x1B[94massert#x1B[39;49;00m solution #x1B[95mis#x1B[39;49;00m #x1B[95mnot#x1B[39;49;00m #x1B[94mNone#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
    #x1B[90m#x1B[39;49;00m
        #x1B[90m# backends may select different tiles, and differ in their ability to#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m# maximize the total tile value, so we can, at best, include known values#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m# for different solvers and use this as a range for any others. The exact#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        #x1B[90m# sets differ based on the tiles selected.#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
        expected_tile_sum = {#x1B[90m#x1B[39;49;00m
            MILPSolver.CBC: #x1B[94m515#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
            #x1B[90m# MILPSolver.GLPK_MI  is either 515 _or_ 589, depending on the exact version installed.#x1B[39;49;00m#x1B[90m#x1B[39;49;00m
            MILPSolver.SCIPY: #x1B[94m515#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
            MILPSolver.HIGHS: #x1B[94m589#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
            MILPSolver.SCIP: #x1B[94m589#x1B[39;49;00m,#x1B[90m#x1B[39;49;00m
        }#x1B[90m#x1B[39;49;00m
        #x1B[94mif#x1B[39;49;00m expected := expected_tile_sum.get(ruleset.backend):#x1B[90m#x1B[39;49;00m
>           #x1B[94massert#x1B[39;49;00m #x1B[96msum#x1B[39;49;00m(solution.tiles) == expected#x1B[90m#x1B[39;49;00m
#x1B[1m#x1B[31mE           assert 515 == 589#x1B[0m
#x1B[1m#x1B[31mE            +  where 515 = sum([<Black 1 (1)>, <Black 3 (3)>, <Black 4 (4)>, <Black 10 (10)>, <Blue 1 (14)>, <Blue 2 (15)>, ...])#x1B[0m
#x1B[1m#x1B[31mE            +    where [<Black 1 (1)>, <Black 3 (3)>, <Black 4 (4)>, <Black 10 (10)>, <Blue 1 (14)>, <Blue 2 (15)>, ...] = ProposedSolution(tiles=[<Black 1 (1)>, <Black 3 (3)>, <Black 4 (4)>, <Black 10 (10)>, <Blue 1 (14)>, <Blue 2 (15)>, <Blue 8 (21)>, <Blue 10 (23)>, <Blue 13 (26)>, <Orange 3 (29)>, <Orange 5 (31)>, <Orange 7 (33)>, <Orange 7 (33)>, <Orange 8 (34)>, <Orange 9 (35)>, <Orange 9 (35)>, <Orange 12 (38)>, <Red 2 (41)>, <Red 4 (43)>, <Red 7 (46)>], sets=[(<Black 1 (1)>, <Black 2 (2)>, <Black 3 (3)>, <Black 4 (4)>), (<Black 1 (1)>, <Blue 1 (14)>, <Joker (53)>), (<Black 3 (3)>, <Blue 3 (16)>, <Orange 3 (29)>), (<Black 4 (4)>, <Blue 4 (17)>, <Red 4 (43)>), (<Black 5 (5)>, <Blue 5 (18)>, <Red 5 (44)>), (<Black 6 (6)>, <Black 7 (7)>, <Black 8 (8)>, <Black 9 (9)>, <Black 10 (10)>), (<Black 13 (13)>, <Blue 13 (26)>, <Red 13 (52)>), (<Blue 2 (15)>, <Orange 2 (28)>, <Red 2 (41)>), (<Blue 5 (18)>, <Blue 6 (19)>, <Blue 7 (20)>, <Blue 8 (21)>), (<Blue 8 (21)>, <Blue 9 (22)>, <Blue 10 (23)>), (<Orange 3 (29)>, <Orange 4 (30)>, <Orange 5 (31)>), (<Orange 7 (33)>, <Orange 8 (34)>, <Orange 9 (35)>), (<Orange 7 (33)>, <Orange 8 (34)>, <Orange 9 (35)>), (<Orange 10 (36)>, <Orange 11 (37)>, <Orange 12 (38)>, <Orange 13 (39)>), (<Red 7 (46)>, <Red 8 (47)>, <Red 9 (48)>, <Red 10 (49)>)], free_jokers=0).tiles#x1B[0m

#x1B[1m#x1B[31mtests\test_ruleset.py#x1B[0m:460: AssertionError

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