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feat(python): add alloc gate scenarios for 3.14/3.15 migration
Add paired python_alloc scenarios asserting alloc-space and alloc-samples with thread-name labels, reusing the python_basic_memory workload. Gate grows from 12 to 14 scenarios.
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‎README.md‎

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@@ -77,7 +77,7 @@ Both use [dd-octo-sts](https://github.com/DataDog/dd-octo-sts-action) (`dd-trace
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**Inputs:**
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- `dd_trace_py_commit_sha` — commit to test (required)
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- `test_scenarios` — regexp passed to `TEST_SCENARIOS` (dd-trace-py passes the [8-scenario 3.14/3.15 migration gate](scenarios/python_downstream_gate/README.md); the downstream workflow default alone is `python.*`)
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- `test_scenarios` — regexp passed to `TEST_SCENARIOS` (dd-trace-py passes the [10-scenario 3.14/3.15 migration gate](scenarios/python_downstream_gate/README.md); the downstream workflow default alone is `python.*`)
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## Creating new tests
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‎scenarios/python_alloc_3.14/Dockerfile‎

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ARG BASE_IMAGE="prof-python-3.14"
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FROM $BASE_IMAGE
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COPY ./scenarios/python_alloc_3.14/requirements.txt /app/requirements.txt
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RUN pip install -r /app/requirements.txt
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COPY ./scenarios/python_alloc_3.14/main.py /app/main.py
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WORKDIR /app
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ENV DD_PROFILING_STACK_ENABLED=false
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ENV DD_PROFILING_LOCK_ENABLED=false
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CMD python main.py

‎scenarios/python_alloc_3.14/README.md‎

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## Allocation profiling (3.14 baseline)
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Validates that the Datadog Python profiler's **memory collector** reports
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`alloc-space` and `alloc-samples` with correct call stacks and `thread name`
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labels. This is the **3.14 baseline** half of the `3.14 -> 3.15` migration pair
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(see `python_alloc_3.15`).
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Reuses the workload from `scenarios/python_basic_memory_3.11`: two allocation
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sites with a 1:3 byte ratio (`allocate_memory_1` / `allocate_memory_2`).
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Stack and lock collectors are disabled to isolate allocation samples.
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## Expected profile
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Assertions match `python_basic_memory_3.11` (stable sampling proportions for
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`alloc-samples` and `alloc-space`).
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## Notes
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The 3.14 scenario runs on prof-correctness `main` CI (PyPI ddtrace). The 3.15
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candidate runs only via the dd-trace-py downstream gate (`DDTRACE_INSTALL_URL`).

‎scenarios/python_alloc_3.14/expected_profile.json‎

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{
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"test_name": "python_alloc_3.14",
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"pprof-regex": "",
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"stacks": [
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{
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"profile-type": "alloc-samples",
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"pprof-regex": "",
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"stack-content": [
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{
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"regular_expression": "^\u003cmodule\u003e;run;allocate_memory_1.*$",
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"percent": 35,
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"error_margin": 5,
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"labels": [
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{
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"key": "thread name",
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"values": [
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"MainThread"
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],
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"values_regex": ""
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}
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]
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}
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]
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},
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{
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"profile-type": "alloc-samples",
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"pprof-regex": "",
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"stack-content": [
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{
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"regular_expression": "^\u003cmodule\u003e;run;allocate_memory_2.*$",
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"percent": 45,
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"error_margin": 5,
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"labels": [
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{
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"key": "thread name",
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"values": [
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"MainThread"
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],
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"values_regex": ""
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}
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]
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}
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]
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},
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{
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"profile-type": "alloc-samples",
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"pprof-regex": "",
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"stack-content": [
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{
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"regular_expression": "^.*__init__;.*grow_list.*$",
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"percent": 19,
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"error_margin": 5,
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"labels": [
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{
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"key": "thread name",
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"values": [
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"MainThread"
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],
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"values_regex": ""
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}
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]
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}
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]
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},
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{
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"profile-type": "alloc-space",
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"pprof-regex": "",
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"stack-content": [
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{
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"regular_expression": "^\u003cmodule\u003e;run;allocate_memory_1.*$",
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"percent": 25,
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"error_margin": 5,
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"labels": [
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{
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"key": "thread name",
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"values": [
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"MainThread"
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],
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"values_regex": ""
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}
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]
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}
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]
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},
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{
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"profile-type": "alloc-space",
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"pprof-regex": "",
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"stack-content": [
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{
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"regular_expression": "^\u003cmodule\u003e;run;allocate_memory_2.*$",
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"percent": 75,
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"error_margin": 5,
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"labels": [
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{
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"key": "thread name",
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"values": [
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"MainThread"
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],
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"values_regex": ""
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}
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]
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}
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]
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},
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{
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"profile-type": "alloc-space",
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"pprof-regex": "",
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"stack-content": [
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{
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"regular_expression": "^.*grow_list.*$",
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"percent": 3,
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"error_margin": 3,
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"labels": [
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{
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"key": "thread name",
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"values": [
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"MainThread"
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],
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"values_regex": ""
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}
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]
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}
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]
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}
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],
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"scale_by_duration": false
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}

‎scenarios/python_alloc_3.14/main.py‎

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from ddtrace.profiling import Profiler
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class Target:
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def __init__(self) -> None:
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self.memory: list[bytearray | None] = []
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self.index = 0
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self.grow_list(target=int(1e6))
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def run(self) -> None:
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while self.memory[-1] is None:
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self.allocate_memory_1(1024)
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self.allocate_memory_2(1024)
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def grow_list(self, target: int) -> None:
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self.memory = [None for _ in range(target)]
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def allocate_memory_1(self, size: int) -> None:
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self.memory[self.index] = bytearray(size)
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self.index += 1
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def allocate_memory_2(self, size: int) -> None:
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self.memory[self.index] = bytearray(3 * size)
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self.index += 1
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if __name__ == "__main__":
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prof = Profiler()
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prof.start()
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Target().run()
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prof.stop()

‎scenarios/python_alloc_3.14/requirements.txt‎

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ddtrace

‎scenarios/python_alloc_3.15/Dockerfile‎

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ARG BASE_IMAGE="prof-python-3.15"
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FROM $BASE_IMAGE
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# ddtrace is pre-installed in the base image when DDTRACE_INSTALL_URL is set
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# (dd-trace-py downstream CI). Do not pip-install here — PyPI wheels may not
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# exist for 3.15 yet.
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COPY ./scenarios/python_alloc_3.15/main.py /app/main.py
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WORKDIR /app
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ENV DD_PROFILING_STACK_ENABLED=false
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ENV DD_PROFILING_LOCK_ENABLED=false
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CMD python main.py

‎scenarios/python_alloc_3.15/README.md‎

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## Allocation profiling (3.15 candidate)
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Validates that the Datadog Python profiler's **memory collector** reports
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`alloc-space` and `alloc-samples` with correct call stacks and `thread name`
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labels. This is the **3.15 candidate** half of the `3.14 -> 3.15` migration pair
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(see `python_alloc_3.14`).
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Reuses the workload from `scenarios/python_basic_memory_3.11`: two allocation
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sites with a 1:3 byte ratio (`allocate_memory_1` / `allocate_memory_2`).
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Stack and lock collectors are disabled to isolate allocation samples.
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## Expected profile
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Assertions match `python_basic_memory_3.11` (stable sampling proportions for
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`alloc-samples` and `alloc-space`).
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## Notes
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This scenario is wheel-only: PyPI ddtrace wheels may not exist for 3.15 yet, so
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it is excluded from prof-correctness `main` CI and runs via the dd-trace-py
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downstream gate (`DDTRACE_INSTALL_URL`).

‎scenarios/python_alloc_3.15/expected_profile.json‎

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{
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"test_name": "python_alloc_3.15",
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"pprof-regex": "",
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"stacks": [
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{
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"profile-type": "alloc-samples",
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"pprof-regex": "",
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"stack-content": [
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{
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"regular_expression": "^\u003cmodule\u003e;run;allocate_memory_1.*$",
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"percent": 35,
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"error_margin": 5,
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"labels": [
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{
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"key": "thread name",
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"values": [
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"MainThread"
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],
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"values_regex": ""
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}
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]
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}
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]
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},
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{
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"profile-type": "alloc-samples",
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"pprof-regex": "",
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"stack-content": [
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{
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"regular_expression": "^\u003cmodule\u003e;run;allocate_memory_2.*$",
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"percent": 45,
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"error_margin": 5,
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"labels": [
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{
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"key": "thread name",
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"values": [
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"MainThread"
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],
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"values_regex": ""
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}
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]
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}
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]
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},
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{
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"profile-type": "alloc-samples",
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"pprof-regex": "",
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"stack-content": [
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{
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"regular_expression": "^.*__init__;.*grow_list.*$",
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"percent": 19,
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"error_margin": 5,
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"labels": [
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{
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"key": "thread name",
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"values": [
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"MainThread"
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],
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"values_regex": ""
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}
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]
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}
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]
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},
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{
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"profile-type": "alloc-space",
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"pprof-regex": "",
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"stack-content": [
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{
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"regular_expression": "^\u003cmodule\u003e;run;allocate_memory_1.*$",
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"percent": 25,
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"error_margin": 5,
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"labels": [
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{
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"key": "thread name",
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"values": [
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"MainThread"
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],
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"values_regex": ""
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}
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]
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}
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]
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},
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{
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"profile-type": "alloc-space",
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"pprof-regex": "",
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"stack-content": [
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{
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"regular_expression": "^\u003cmodule\u003e;run;allocate_memory_2.*$",
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"percent": 75,
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"error_margin": 5,
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"labels": [
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{
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"key": "thread name",
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"values": [
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"MainThread"
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],
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"values_regex": ""
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}
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]
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}
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]
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},
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{
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"profile-type": "alloc-space",
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"pprof-regex": "",
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"stack-content": [
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{
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"regular_expression": "^.*grow_list.*$",
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"percent": 3,
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"error_margin": 3,
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"labels": [
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{
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"key": "thread name",
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"values": [
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"MainThread"
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],
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"values_regex": ""
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}
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]
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}
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]
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}
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],
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"scale_by_duration": false
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}

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