feat(python): add cpu-time gate scenarios for 3.14/3.15 migration

Add paired python_cpu scenarios asserting stack cpu-time samples and
thread-name labels on the migration gate path, growing coverage from 10
to 12 scenarios.

Author: vlad-scherbich

README.md

@@ -55,7 +55,7 @@ Both use [dd-octo-sts](https://github.com/DataDog/dd-octo-sts-action) (`dd-trace
 **Inputs:**
 
 - `dd_trace_py_commit_sha` — commit to test (required)
-- `test_scenarios` — regexp passed to `TEST_SCENARIOS` (dd-trace-py passes the [6-scenario 3.14/3.15 migration gate](scenarios/python_downstream_gate/README.md); the downstream workflow default alone is `python.*`)
+- `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.*`)
 
 ## Creating new tests 
 

scenarios/python_cpu_3.14/Dockerfile

@@ -0,0 +1,15 @@
+ARG BASE_IMAGE="prof-python-3.14"
+FROM $BASE_IMAGE
+
+COPY ./scenarios/python_cpu_3.14/requirements.txt /app/requirements.txt
+RUN pip install -r /app/requirements.txt
+
+COPY ./scenarios/python_cpu_3.14/main.py /app/main.py
+WORKDIR /app
+
+ENV EXECUTION_TIME_SEC=10
+ENV _DD_PROFILING_STACK_ADAPTIVE_SAMPLING_ENABLED=0
+ENV DD_PROFILING_ENABLED=true
+ENV DD_PROFILING_MEMORY_ENABLED=false
+
+CMD ddtrace-run python main.py

scenarios/python_cpu_3.14/README.md

@@ -0,0 +1,24 @@
+## CPU stack profiling (3.14 baseline)
+
+Validates that the Datadog Python profiler's **stack collector** reports
+`cpu-time` samples with correct call stacks and `thread name` labels under a
+CPU-bound workload. This is the **3.14 baseline** half of the `3.14 -> 3.15`
+migration pair (see `python_cpu_3.15`).
+
+Reuses the workload from `scenarios/python_cpu`: two tight loops (`a` and `b`)
+with a 2:1 relative CPU share. Memory profiling is disabled so the assertion
+targets stack samples only.
+
+## Expected profile
+
+- `cpu-time`:
+  - `<module>;.*main;.*b` ~= 66% (`MainThread`)
+  - `<module>;.*main;.*a` ~= 33% (`MainThread`)
+
+`cpu-time` is best-effort per sample, so `error_margin` is generous.
+`scale_by_duration` normalizes across run lengths.
+
+## Notes
+
+The 3.14 scenario runs on prof-correctness `main` CI (PyPI ddtrace). The 3.15
+candidate runs only via the dd-trace-py downstream gate (`DDTRACE_INSTALL_URL`).

scenarios/python_cpu_3.14/expected_profile.json

@@ -0,0 +1,37 @@
+{
+  "test_name": "python_cpu_3.14",
+  "stacks": [
+    {
+      "profile-type": "cpu-time",
+      "stack-content": [
+        {
+          "regular_expression": "<module>;.*main;.*b",
+          "percent": 66,
+          "error_margin": 100,
+          "labels": [
+            {
+              "key": "thread name",
+              "values": [
+                "MainThread"
+              ]
+            }
+          ]
+        },
+        {
+          "regular_expression": "<module>;.*main;.*a",
+          "percent": 33,
+          "error_margin": 100,
+          "labels": [
+            {
+              "key": "thread name",
+              "values": [
+                "MainThread"
+              ]
+            }
+          ]
+        }
+      ]
+    }
+  ],
+  "scale_by_duration": true
+}

scenarios/python_cpu_3.14/main.py

@@ -0,0 +1,30 @@
+import os
+from time import time
+
+
+class CPUBurner:
+    def __init__(self) -> None:
+        self.x = 0
+        self.i = 0
+
+    def a(self) -> None:
+        self.i = 0
+        while self.i < 1000000:
+            self.x += self.i
+            self.i += 1
+
+    def b(self) -> None:
+        self.i = 0
+        while self.i < 2000000:
+            self.x += self.i
+            self.i += 1
+
+    def main(self) -> None:
+        execution_time_sec = float(os.getenv("EXECUTION_TIME_SEC", "10"))
+        end = time() + execution_time_sec
+        while time() < end:
+            self.a()
+            self.b()
+
+
+CPUBurner().main()

scenarios/python_cpu_3.14/requirements.txt

@@ -0,0 +1 @@
+ddtrace

scenarios/python_cpu_3.15/Dockerfile

@@ -0,0 +1,16 @@
+ARG BASE_IMAGE="prof-python-3.15"
+FROM $BASE_IMAGE
+
+# ddtrace is pre-installed in the base image when DDTRACE_INSTALL_URL is set
+# (dd-trace-py downstream CI). Do not pip-install here — PyPI wheels may not
+# exist for 3.15 yet.
+
+COPY ./scenarios/python_cpu_3.15/main.py /app/main.py
+WORKDIR /app
+
+ENV EXECUTION_TIME_SEC=10
+ENV _DD_PROFILING_STACK_ADAPTIVE_SAMPLING_ENABLED=0
+ENV DD_PROFILING_ENABLED=true
+ENV DD_PROFILING_MEMORY_ENABLED=false
+
+CMD ddtrace-run python main.py

scenarios/python_cpu_3.15/README.md

@@ -0,0 +1,25 @@
+## CPU stack profiling (3.15 candidate)
+
+Validates that the Datadog Python profiler's **stack collector** reports
+`cpu-time` samples with correct call stacks and `thread name` labels under a
+CPU-bound workload. This is the **3.15 candidate** half of the `3.14 -> 3.15`
+migration pair (see `python_cpu_3.14`).
+
+Reuses the workload from `scenarios/python_cpu`: two tight loops (`a` and `b`)
+with a 2:1 relative CPU share. Memory profiling is disabled so the assertion
+targets stack samples only.
+
+## Expected profile
+
+- `cpu-time`:
+  - `<module>;.*main;.*b` ~= 66% (`MainThread`)
+  - `<module>;.*main;.*a` ~= 33% (`MainThread`)
+
+`cpu-time` is best-effort per sample, so `error_margin` is generous.
+`scale_by_duration` normalizes across run lengths.
+
+## Notes
+
+This scenario is wheel-only: PyPI ddtrace wheels may not exist for 3.15 yet, so
+it is excluded from prof-correctness `main` CI and runs via the dd-trace-py
+downstream gate (`DDTRACE_INSTALL_URL`).

scenarios/python_cpu_3.15/expected_profile.json

@@ -0,0 +1,37 @@
+{
+  "test_name": "python_cpu_3.15",
+  "stacks": [
+    {
+      "profile-type": "cpu-time",
+      "stack-content": [
+        {
+          "regular_expression": "<module>;.*main;.*b",
+          "percent": 66,
+          "error_margin": 100,
+          "labels": [
+            {
+              "key": "thread name",
+              "values": [
+                "MainThread"
+              ]
+            }
+          ]
+        },
+        {
+          "regular_expression": "<module>;.*main;.*a",
+          "percent": 33,
+          "error_margin": 100,
+          "labels": [
+            {
+              "key": "thread name",
+              "values": [
+                "MainThread"
+              ]
+            }
+          ]
+        }
+      ]
+    }
+  ],
+  "scale_by_duration": true
+}

scenarios/python_cpu_3.15/main.py

@@ -0,0 +1,30 @@
+import os
+from time import time
+
+
+class CPUBurner:
+    def __init__(self) -> None:
+        self.x = 0
+        self.i = 0
+
+    def a(self) -> None:
+        self.i = 0
+        while self.i < 1000000:
+            self.x += self.i
+            self.i += 1
+
+    def b(self) -> None:
+        self.i = 0
+        while self.i < 2000000:
+            self.x += self.i
+            self.i += 1
+
+    def main(self) -> None:
+        execution_time_sec = float(os.getenv("EXECUTION_TIME_SEC", "10"))
+        end = time() + execution_time_sec
+        while time() < end:
+            self.a()
+            self.b()
+
+
+CPUBurner().main()