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{"baseBranch":"main","baseCommit":"1501bff342c55fca79d2687e75f1f1b3382d2fb9","createdAt":"2024-12-18T23:20:16.713593Z","headSha":"00b76400e6565fe94a9dc91108885ccf41f91c75","id":"08473384-2b72-44ff-9215-045d36f9e95b","priority":"200","pullRequestNumber":"11498","queuedAt":"2024-12-18T23:20:16.712998Z","status":"STATUS_QUEUED"}
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releasenotes/notes/fix-celery-closed-spans-34ff43868c1e33b8.yaml
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--- | ||
fixes: | ||
- | | ||
tracing(celery): Fixes an issue where ``celery.apply`` spans from Celery prerun got closed too soon leading to span tags being missing. |
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from tasks import fn_a | ||
from tasks import fn_b | ||
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(fn_a.si() | fn_b.si()).delay() |
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from celery import Celery | ||
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app = Celery("tasks") | ||
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@app.task(name="tests.contrib.celery.tasks.fn_a") | ||
def fn_a(): | ||
return "a" | ||
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@app.task(name="tests.contrib.celery.tasks.fn_b") | ||
def fn_b(): | ||
return "b" |
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import os | ||
import re | ||
import subprocess | ||
import time | ||
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from celery import Celery | ||
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# Ensure that when we call Celery chains, the root span has celery specific span tags | ||
# The test_integration.py setup doesn't perfectly mimic the condition of a worker process running. | ||
# This test runs the worker as a side so we can check the tracer logs afterwards to ensure expected span results. | ||
# See https://github.com/DataDog/dd-trace-py/issues/11479 | ||
def test_task_chain_task_call_task(): | ||
app = Celery("tasks") | ||
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celery_worker_cmd = "ddtrace-run celery -A tasks worker -c 1 -l DEBUG -n uniquename1 -P solo" | ||
celery_task_runner_cmd = "ddtrace-run python run_tasks.py" | ||
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# The commands need to run from the directory where this test file lives | ||
current_directory = str(os.path.dirname(__file__)) | ||
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worker_process = subprocess.Popen( | ||
celery_worker_cmd.split(), | ||
stdout=subprocess.PIPE, | ||
stderr=subprocess.PIPE, | ||
preexec_fn=os.setsid, | ||
close_fds=True, | ||
cwd=current_directory, | ||
) | ||
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max_wait_time = 10 | ||
waited_so_far = 0 | ||
# {app.control.inspect().active() returns {'celery@uniquename1': []} when the worker is running} | ||
while app.control.inspect().active() is None and waited_so_far < max_wait_time: | ||
time.sleep(1) | ||
waited_so_far += 1 | ||
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# The task should only run after the Celery worker has sufficient time to start up | ||
task_runner_process = subprocess.Popen( | ||
celery_task_runner_cmd.split(), | ||
stdout=subprocess.PIPE, | ||
stderr=subprocess.PIPE, | ||
preexec_fn=os.setsid, | ||
close_fds=True, | ||
cwd=current_directory, | ||
) | ||
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task_runner_process.wait() | ||
# Kill the process so it starts to send traces to the Trace Agent | ||
worker_process.kill() | ||
worker_logs = worker_process.stderr.read() | ||
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# Check that the root span was created with one of the Celery specific tags, such as celery.correlation_id | ||
# Some versions of python seem to require escaping when using `re.search`: | ||
old_pattern_match = r"resource=\\'tests.contrib.celery.tasks.fn_a\\' type=\\'worker\\' .* tags=.*correlation_id.*" | ||
new_pattern_match = r"resource=\'tests.contrib.celery.tasks.fn_a\' type=\'worker\' .* tags=.*correlation_id.*" | ||
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pattern_exists = ( | ||
re.search(old_pattern_match, str(worker_logs)) is not None | ||
or re.search(new_pattern_match, str(worker_logs)) is not None | ||
) | ||
assert pattern_exists is not None |