CompatHelper: add new compat entry for DynamicPPL at version 0.42 for package test, (keep existing compat)

[github-actions]

This pull request sets the compat entry for the DynamicPPL package to 0.42 for package test.
This keeps the compat entries for earlier versions.

Note: I have not tested your package with this new compat entry.
It is your responsibility to make sure that your package tests pass before you merge this pull request.
Note: Consider registering a new release of your package immediately after merging this PR, as downstream packages may depend on this for tests to pass.

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 81.58%. Comparing base (9347d11) to head (721acb0).

Additional details and impacted files

@@           Coverage Diff           @@
##             main    #1413   +/-   ##
=======================================
  Coverage   81.58%   81.58%           
=======================================
  Files          50       50           
  Lines        3578     3578           
=======================================
  Hits         2919     2919           
  Misses        659      659           

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[github-actions]

DynamicPPL.jl documentation for PR #1413 is available at:
https://TuringLang.github.io/DynamicPPL.jl/previews/PR1413/

[github-actions]

Benchmarks @ 721acb0

Performance Ratio: gradient time divided by log-density time.

For very small models these ratios are noisy across runs and machines; raw primal and gradient timings are more reliable. The benchmarks are aimed at DynamicPPL developers and mainly catch obvious allocation or type-stability regressions. See benchmark notes for details.

===================================================================================================
                                               eval                       gradient                 
                                            ----------  -------------------------------------------
Model                        dim    linked      primal     FwdDiff    RvsDiff    Mooncake    Enzyme
---------------------------------------------------------------------------------------------------
Simple assume observe*         1     false     4.63 ns       12.52    1546.29       35.01     12.23
Simple assume observe*         1      true     4.63 ns       12.57    1672.04       35.41     12.13
Smorgasbord                  201     false     5.94 μs       75.25     133.76        6.78      9.63
Smorgasbord                  201      true     7.62 μs       73.69     141.07        6.16      6.88
Loop univariate 1k          1000     false     17.8 μs      934.50     301.80        8.58      6.53
Loop univariate 1k          1000      true     19.2 μs     1393.53     279.89        8.07      6.00
Multivariate 1k             1000     false     23.6 μs      305.96      72.90        9.17      2.96
Multivariate 1k             1000      true     24.1 μs      274.57      62.18        9.11      2.90
Loop univariate 10k        10000     false    172.0 μs    11952.71     322.87        8.91      6.67
Loop univariate 10k        10000      true    186.0 μs    11740.88     297.96        8.23      6.07
Multivariate 10k           10000     false    196.0 μs     4853.77      89.50       11.36      2.29
Multivariate 10k           10000      true    196.0 μs     4897.79      89.83       11.30      2.24
Dynamic                       15     false     1.37 μs         err      41.92       40.13     11.04
Dynamic                       10      true     1.95 μs        1.90      55.62       15.27     19.17
Submodel*                      1     false     4.63 ns       12.61    1675.98       35.42     12.25
Submodel*                      1      true     4.63 ns       12.56    1770.72       35.51     12.32
LDA                           12      true     22.8 μs        0.45       1.97       33.59       err
===================================================================================================

Main @ 9347d11

===================================================================================================
                                               eval                       gradient                 
                                            ----------  -------------------------------------------
Model                        dim    linked      primal     FwdDiff    RvsDiff    Mooncake    Enzyme
---------------------------------------------------------------------------------------------------
Simple assume observe*         1     false     4.64 ns       12.53    1527.06       35.25     12.25
Simple assume observe*         1      true     4.63 ns       12.57    1673.50       38.21     12.25
Smorgasbord                  201     false     5.93 μs       71.73     135.56        6.97      9.73
Smorgasbord                  201      true     7.59 μs       78.79     142.94        6.13      6.85
Loop univariate 1k          1000     false     17.9 μs      967.19     301.57        8.19      4.86
Loop univariate 1k          1000      true     19.2 μs     1378.38     279.78        7.50      6.05
Multivariate 1k             1000     false     22.8 μs      338.72      75.58        9.71      3.16
Multivariate 1k             1000      true     25.2 μs      345.64      63.02        8.93      2.93
Loop univariate 10k        10000     false    174.0 μs    11775.06     330.87        8.54      4.95
Loop univariate 10k        10000      true    186.0 μs    11820.43     309.15        7.81      6.16
Multivariate 10k           10000     false    198.0 μs     5042.99      91.28       10.70      2.17
Multivariate 10k           10000      true    197.0 μs     5336.03      85.50       11.47      2.28
Dynamic                       15     false     1.36 μs         err      43.35       14.74     11.18
Dynamic                       10      true     1.98 μs        1.93      57.08       13.51     19.25
Submodel*                      1     false     4.63 ns       12.54    1728.48       35.30     12.37
Submodel*                      1      true     4.64 ns       12.58    1855.97       38.80     12.44
LDA                           12      true     22.5 μs        0.63       2.08       32.61       err
===================================================================================================

Environment

Julia Version 1.11.9
Commit 53a02c0720c (2026-02-06 00:27 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 4 × AMD EPYC 7763 64-Core Processor
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)