chore(ci): enable Python 3.15 support for dramatiq

[wantsui]

Description

Builds on #19879, which already enabled Dramatiq testing on Python 3.14 and added the 17f991e lockfile. This PR will unblock the integrations CI for dramatiq (and later other integrations).

This PR enables the next runtime only:

• Adds Python 3.15 only to the Dramatiq Riot environment; the global repository runtime list remains capped at Python 3.14 until closer to the Python 3.15 release.
• Extends the latest-package Dramatiq environment from Python 3.14 through Python 3.15. This is our test to make sure CI isn't totally broken.
• Adds the generated Dramatiq Python 3.15 lockfile via a container using the piptools that work for Python 3.15
  Related PRs:
  ci(testrunner): install pip-tools for Python 3.15 #19977
  ci: update testrunner image #19984

Testing

• scripts/lint fmt -- riotfile.py
• scripts/lint riot
• scripts/lint checks
• scripts/run-tests --list tests/contrib/dramatiq/ confirms the existing Python 3.14 venv 17f991e and new Python 3.15 venv 4112544
• Regenerated 4112544 with Riot under Python 3.15; the lockfile was unchanged

Risks

Low integration risk because this changes only Dramatiq Riot coverage and generated metadata. Python 3.15 remains enabled per integration while the global matrix stays capped at 3.14.

Additional Notes

• Python 3.14 support was merged separately in test(dramatiq): enable tests for Python 3.14 #19879 and is not added by this PR.
• Base branch: main.
• Local Python 3.15 installation currently requires the documented PIP_IGNORE_REQUIRES_PYTHON=1 override because the package metadata still declares Requires-Python <3.15.

Historical CI error for 3.15

Issue 1: Injection Assembly errors (fixed in this PR)
There's 174 failures at the moment:

Based on https://gitlab.ddbuild.io/DataDog/apm-reliability/dd-trace-py/-/jobs/1995599108 , we can't use INJECTION_ASSEMBLY

^^^^^^^^^
  File "/go/src/github.com/DataDog/apm-reliability/dd-trace-py/ddtrace/internal/coverage/instrumentation_py3_12.py", line 19, in <module>
    from ddtrace.internal.coverage.import_instrumentation_py3_12 import ImportName
  File "/go/src/github.com/DataDog/apm-reliability/dd-trace-py/ddtrace/internal/coverage/import_instrumentation_py3_12.py", line 9, in <module>
    from ddtrace.internal.bytecode_injection import INJECTION_ASSEMBLY
ImportError: cannot import name 'INJECTION_ASSEMBLY' from 'ddtrace.internal.bytecode_injection' (/go/src/github.com/DataDog/apm-reliability/dd-trace-py/ddtrace/internal/bytecode_injection/__init__.py)
Test failed with exit code 1

Issue 2: Lock files
Regenerated after the pip-tools PR.

[cit-pr-commenter-54b7da]

Codeowners resolved as

Resolved from the full PR diff against vlad/py315-riotfile using the target branch CODEOWNERS file.
CODEOWNERS team requests not listed below are not required by the current file set.

.riot/requirements/128b106.txt                                          @DataDog/apm-python
.riot/requirements/1381214.txt                                          @DataDog/apm-python
.riot/requirements/14116fa.txt                                          @DataDog/apm-python
.riot/requirements/17f991e.txt                                          @DataDog/apm-python
.riot/requirements/19508cd.txt                                          @DataDog/apm-python
.riot/requirements/4112544.txt                                          @DataDog/apm-python
.riot/requirements/638973a.txt                                          @DataDog/apm-python
ddtrace/internal/coverage/import_instrumentation_py3_12.py              @DataDog/ci-app-libraries
ddtrace/internal/coverage/instrumentation_py3_12.py                     @DataDog/ci-app-libraries
riotfile.py                                                             @DataDog/apm-python
scripts/integration_registry/registry.yaml                              @DataDog/apm-idm-python
supported_versions.json                                                 @DataDog/apm-core-python @DataDog/apm-idm-python
tests/coverage/test_import_dependency_tracking.py                       @DataDog/ci-app-libraries
tests/coverage/test_import_instrumentation_py312.py                     @DataDog/ci-app-libraries

[cit-pr-commenter-54b7da]

Dependency direction analysis

⚠️ Existing dependency direction violations

There are 230 dependency direction violations that already exist on the base branch and have not been changed by this PR.

Show existing violations (showing 5 of 230 highest severity)

ddtrace.internal.tracemethods -×-> ddtrace.trace  (internal-core -> product:tracing, score=134)
ddtrace.llmobs._integrations.openai -×-> ddtrace.trace  (product:llmobs -> product:tracing, score=132)
ddtrace.profiling.collector.pytorch -×-> ddtrace.trace  (product:profiling -> product:tracing, score=132)
ddtrace.appsec._listeners -×-> ddtrace.trace  (product:appsec -> product:tracing, score=132)
ddtrace.internal.openfeature._span_enrichment -×-> ddtrace.trace  (product:openfeature -> product:tracing, score=132)

To see all violations, download the layers-base.json and layers-pr.json artifacts from this CI job and run:

uv run --script scripts/import-analysis/layers.py compare layers-base.json layers-pr.json

[cit-pr-commenter-54b7da]

Circular import analysis

⚠️ Existing circular imports

There are 3 circular imports that already exist on the base branch and have not been changed by this PR.

ddtrace.llmobs -> ddtrace.llmobs._evaluators -> ddtrace.llmobs._evaluators.format -> ddtrace.llmobs._experiment -> ddtrace.llmobs
ddtrace.errortracking._handled_exceptions.bytecode_injector -> ddtrace.errortracking._handled_exceptions.callbacks -> ddtrace.errortracking._handled_exceptions.collector -> ddtrace.errortracking._handled_exceptions.bytecode_reporting -> ddtrace.errortracking._handled_exceptions.bytecode_injector
ddtrace.appsec._asm_request_context -> ddtrace.appsec._iast._iast_request_context_base -> ddtrace.appsec._iast._iast_env -> ddtrace.appsec._iast.reporter -> ddtrace.appsec._exploit_prevention.stack_traces -> ddtrace.appsec._asm_request_context

[pr-commenter]

Benchmarks

Benchmark execution time: 2026-09-04 21:34:38

Comparing candidate commit 2542bca in PR branch codex-dramatiq-py315 with baseline commit 8c7799f in branch vlad/py315-riotfile.

📊 Benchmarking dashboard

Found 0 performance improvements and 8 performance regressions! Performance is the same for 577 metrics, 10 unstable metrics, 3 known flaky benchmarks, 15 flaky benchmarks without significant changes.

Explanation

This is an A/B test comparing a candidate commit's performance against that of a baseline commit. Performance changes are noted in the tables below as:

• 🟩 = significantly better candidate vs. baseline
• 🟥 = significantly worse candidate vs. baseline

We compute a confidence interval (CI) over the relative difference of means between metrics from the candidate and baseline commits, considering the baseline as the reference.

If the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD), the change is considered significant.

Feel free to reach out to #apm-benchmarking-platform on Slack if you have any questions.

More details about the CI and significant changes

You can imagine this CI as a range of values that is likely to contain the true difference of means between the candidate and baseline commits.

CIs of the difference of means are often centered around 0%, because often changes are not that big:

---------------------------------(------|---^--------)-------------------------------->
                              -0.6%    0%  0.3%     +1.2%
                                 |          |        |
         lower bound of the CI --'          |        |
sample mean (center of the CI) -------------'        |
         upper bound of the CI ----------------------'

As described above, a change is considered significant if the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD).

For instance, for an execution time metric, this confidence interval indicates a significantly worse performance:

----------------------------------------|---------|---(---------^---------)---------->
                                       0%        1%  1.3%      2.2%      3.1%
                                                  |   |         |         |
       significant impact threshold --------------'   |         |         |
                      lower bound of CI --------------'         |         |
       sample mean (center of the CI) --------------------------'         |
                      upper bound of CI ----------------------------------'

scenario:httppropagationinject-ids_only

• 🟥 execution_time [+2.026µs; +2.207µs] or [+11.887%; +12.947%]

scenario:iastaspects-join_aspect

• 🟥 execution_time [+44.982µs; +48.478µs] or [+20.568%; +22.167%]

scenario:iastaspects-title_aspect

• 🟥 execution_time [+64.402µs; +69.707µs] or [+23.485%; +25.420%]

scenario:iastaspectsospath-ospathbasename_aspect

• 🟥 execution_time [+118.694µs; +126.103µs] or [+28.713%; +30.505%]

scenario:iastaspectssplit-rsplit_aspect

• 🟥 execution_time [+15.697µs; +20.958µs] or [+11.199%; +14.952%]

scenario:samplingrules-high_match

• 🟥 execution_time [+11.957µs; +13.678µs] or [+7.624%; +8.720%]

scenario:telemetryaddmetric-1-count-metric-1-times

• 🟥 execution_time [+496.043ns; +535.804ns] or [+17.899%; +19.333%]

scenario:tracer-small

• 🟥 execution_time [+37.287µs; +40.410µs] or [+11.435%; +12.393%]

Unstable benchmarks

These benchmarks have a confidence interval too wide to call a change; treat them as noise rather than signal.

scenario:coreapiscenario-context_with_data_listeners

• unstable execution_time [-686.761ns; +778.028ns] or [-6.206%; +7.031%]

scenario:coreapiscenario-core_dispatch_1_listener

• unstable execution_time [-29.965ns; +35.767ns] or [-4.918%; +5.870%]

scenario:coreapiscenario-core_dispatch_50_listeners

• unstable execution_time [-1639.219ns; +1650.695ns] or [-9.647%; +9.714%]

scenario:coreapiscenario-core_dispatch_exception_listeners

• unstable execution_time [-1298.467ns; +1189.946ns] or [-9.938%; +9.107%]

scenario:coreapiscenario-core_dispatch_listeners

• unstable execution_time [-328.056ns; +322.495ns] or [-8.954%; +8.802%]

scenario:coreapiscenario-core_dispatch_no_args_listeners

• unstable execution_time [-251.773ns; +260.930ns] or [-8.636%; +8.950%]

scenario:coreapiscenario-core_dispatch_with_results_1_listener

• unstable execution_time [-81.865ns; +66.627ns] or [-7.118%; +5.793%]

scenario:coreapiscenario-core_dispatch_with_results_50_listeners

• unstable execution_time [-4021.878ns; +4032.007ns] or [-9.764%; +9.789%]

scenario:coreapiscenario-core_dispatch_with_results_listeners

• unstable execution_time [-761.311ns; +789.127ns] or [-9.403%; +9.747%]

scenario:packagesupdateimporteddependencies-import_many_stdlib_cached

• unstable execution_time [-58.278µs; +53.172µs] or [-9.979%; +9.105%]

Known flaky benchmarks

These benchmarks are marked as flaky and will not trigger a failure. Modify FLAKY_BENCHMARKS_REGEX to control which benchmarks are marked as flaky.

scenario:iastaspects-casefold_noaspect

• 🟥 execution_time [+39.950µs; +44.668µs] or [+16.334%; +18.263%]

scenario:iastaspects-ljust_noaspect

• 🟥 execution_time [+41.965µs; +48.514µs] or [+14.238%; +16.460%]

scenario:span-start

• 🟥 execution_time [+1.581ms; +1.748ms] or [+10.961%; +12.120%]

Known flaky benchmarks without significant changes:

• scenario:errortrackingflasksqli-baseline
• scenario:flasksimple-iast-get
• scenario:iastaspects-casefold_aspect
• scenario:iastaspects-index_aspect
• scenario:iastaspects-lower_aspect
• scenario:iastaspects-replace_aspect
• scenario:iastaspects-swapcase_aspect
• scenario:iastaspects-title_noaspect
• scenario:iastaspects-translate_aspect
• scenario:iastaspects-translate_noaspect
• scenario:iastaspects-upper_noaspect
• scenario:packagespackageforrootmodulemapping-cache_off
• scenario:packagespackageforrootmodulemapping-cache_on
• scenario:sethttpmeta-all-enabled
• scenario:telemetryaddmetric-record-100-metrics

[emmettbutler]

Looks good aside from the huge comment

[datadog-official]

The new Python 3.15 Dramatiq lock pins 2.2.0. The Riot environment requests the latest release, and the other changed lockfiles and registry use 2.2.1.

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[datadog-official]

More details

The Python 3.15 Dramatiq matrix agrees with the generated dependency files and the coverage fallback. The static review identifies no concrete regression.

Was this helpful? React 👍 or 👎

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