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Hi! I might be missing something silly, hope you c...
# ask-community
m
Hi! I might be missing something silly, hope you can help. I have an image pushed to my Google Cloud Artifacts Registry (
europe-docker.pkg.dev/project/folder-staging/image_name:latest
), previously this image had an issue as it was missing a dependency (
pandas
lib) - I fixed this and the image was re-deployed via our CI, I've verified that the image now does have the dependency installed correctly. The CI was also triggered to re-deploy the flow by calling the following function:
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def deploy_projects_observability_export_flow():
    projects_observability_export_flow.deploy(
        name="projects_observability_export_flow_k8s_deployment",
        work_pool_name="default-worker-pool",
        image="europe-docker.pkg.dev/***/prefect-runners-staging/default:latest",
        tags=["staging"],
        schedule=CronSchedule(cron="0 0 * * *", timezone="UTC"),
        job_variables={
            "cpu_request": "110m",
            "mem_request": "128Mi",
            "cpu_limit": "1200m",
            "mem_limit": "8Gi",
        },
    )
However, the flow runs that are set to leverage this image keep showing the 
ModuleNotFound
error. Do you happen to know what I'm missing?
k
do you know what the image pull policy is? is it possible a cached image is being used?
m
I don't think that's the issue, I just created a brand new image with a different path, and it still failed for the same reason
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k describe job -n prefect phenomenal-sidewinder-csnmg
Name:             phenomenal-sidewinder-csnmg
Namespace:        prefect
Selector:         <http://batch.kubernetes.io/controller-uid=32b709ed-0221-40e2-94af-0c99a6864fc0|batch.kubernetes.io/controller-uid=32b709ed-0221-40e2-94af-0c99a6864fc0>
Labels:           <http://prefect.io/deployment-id=99693312-dfdf-458b-ba2a-fe9a36423863|prefect.io/deployment-id=99693312-dfdf-458b-ba2a-fe9a36423863>
                  <http://prefect.io/deployment-name=projects_observability_export_flow_k8s_deployment|prefect.io/deployment-name=projects_observability_export_flow_k8s_deployment>
                  <http://prefect.io/deployment-updated=2024-05-22t16-28-20.988838z|prefect.io/deployment-updated=2024-05-22t16-28-20.988838z>
                  <http://prefect.io/flow-id=05196d14-2c87-408d-811b-0f7f543717cf|prefect.io/flow-id=05196d14-2c87-408d-811b-0f7f543717cf>
                  <http://prefect.io/flow-name=projects_observability_export_flow|prefect.io/flow-name=projects_observability_export_flow>
                  <http://prefect.io/flow-run-id=a6344f2c-32ba-4300-9e6e-49dadfb62054|prefect.io/flow-run-id=a6344f2c-32ba-4300-9e6e-49dadfb62054>
                  <http://prefect.io/flow-run-name=phenomenal-sidewinder|prefect.io/flow-run-name=phenomenal-sidewinder>
                  <http://prefect.io/version=2.19.1|prefect.io/version=2.19.1>
Annotations:      <http://batch.kubernetes.io/job-tracking|batch.kubernetes.io/job-tracking>:
Parallelism:      1
Completions:      1
Completion Mode:  NonIndexed
Start Time:       Wed, 22 May 2024 18:29:19 +0200
Completed At:     Wed, 22 May 2024 18:29:38 +0200
Duration:         19s
Pods Statuses:    0 Active (0 Ready) / 1 Succeeded / 0 Failed
Pod Template:
  Labels:  <http://batch.kubernetes.io/controller-uid=32b709ed-0221-40e2-94af-0c99a6864fc0|batch.kubernetes.io/controller-uid=32b709ed-0221-40e2-94af-0c99a6864fc0>
           <http://batch.kubernetes.io/job-name=phenomenal-sidewinder-csnmg|batch.kubernetes.io/job-name=phenomenal-sidewinder-csnmg>
           controller-uid=32b709ed-0221-40e2-94af-0c99a6864fc0
           job-name=phenomenal-sidewinder-csnmg
  Containers:
   prefect-job:
    Image:      europe-docker.pkg.dev/cambium-earth/prefect-runners-staging/projects_observability:latest
    Port:       <none>
    Host Port:  <none>
    Args:
      prefect
      flow-run
      execute
    Limits:
      cpu:     1200m
      memory:  8Gi
    Requests:
      cpu:     110m
      memory:  128Mi
    Environment:
      PREFECT_DEBUG_MODE:               False
      PREFECT_API_URL:                  <https://api.prefect.cloud/api/accounts/XXXXXX/workspaces/XXXXX>
      PREFECT_API_KEY:                  pnu_XXXXX

      PREFECT_API_ENABLE_HTTP2:         True
      PREFECT_WORKER_QUERY_SECONDS:     5.0
      PREFECT_WORKER_PREFETCH_SECONDS:  10.0
      PREFECT__FLOW_RUN_ID:             a6344f2c-32ba-4300-9e6e-49dadfb62054
    Mounts:                             <none>
  Volumes:                              <none>
Events:
  Type    Reason            Age   From            Message
  ----    ------            ----  ----            -------
  Normal  SuccessfulCreate  62s   job-controller  Created pod: phenomenal-sidewinder-csnmg-bx94s
  Normal  Completed         42s   job-controller  Job completed
this is the error trace:
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Worker 'KubernetesWorker b1900e5c-ad9d-4be0-9998-e1a160579573' submitting flow run 'a6344f2c-32ba-4300-9e6e-49dadfb62054'
06:29:19 PM
prefect.flow_runs.worker
Creating Kubernetes job...
06:29:19 PM
prefect.flow_runs.worker
Job 'phenomenal-sidewinder-csnmg': Pod has status 'Pending'.
06:29:19 PM
prefect.flow_runs.worker
Completed submission of flow run 'a6344f2c-32ba-4300-9e6e-49dadfb62054'
06:29:19 PM
prefect.flow_runs.worker
Job 'phenomenal-sidewinder-csnmg': Pod has status 'Running'.
06:29:22 PM
prefect.flow_runs.worker
Opening process...
06:29:25 PM
prefect.flow_runs.runner
Downloading flow code from storage at '.'
06:29:28 PM
prefect.flow_runs
Flow could not be retrieved from deployment.
Traceback (most recent call last):
  File "", line 940, in exec_module
  File "", line 241, in _call_with_frames_removed
  File "/opt/prefect/data-canopy/data-flows/dataflows/flows/projects_observability_export_flow.py", line 1, in 
    import pandas as pd
ModuleNotFoundError: No module named 'pandas'

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/usr/local/lib/python3.11/site-packages/prefect/engine.py", line 420, in retrieve_flow_then_begin_flow_run
    else await load_flow_from_flow_run(flow_run, client=client)
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/prefect/client/utilities.py", line 100, in with_injected_client
    return await fn(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/prefect/deployments/deployments.py", line 317, in load_flow_from_flow_run
    flow = await run_sync_in_worker_thread(load_flow_from_entrypoint, str(import_path))
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/prefect/utilities/asyncutils.py", line 132, in run_sync_in_worker_thread
    return await anyio.to_thread.run_sync(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/anyio/to_thread.py", line 33, in run_sync
    return await get_asynclib().run_sync_in_worker_thread(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/anyio/_backends/_asyncio.py", line 877, in run_sync_in_worker_thread
    return await future
           ^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/anyio/_backends/_asyncio.py", line 807, in run
    result = context.run(func, *args)
             ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/prefect/flows.py", line 1682, in load_flow_from_entrypoint
    flow = import_object(entrypoint)
           ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/prefect/utilities/importtools.py", line 201, in import_object
    module = load_script_as_module(script_path)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/prefect/utilities/importtools.py", line 164, in load_script_as_module
    raise ScriptError(user_exc=exc, path=path) from exc
prefect.exceptions.ScriptError: Script at 'data-flows/dataflows/flows/projects_observability_export_flow.py' encountered an exception: ModuleNotFoundError("No module named 'pandas'")
06:29:28 PM
prefect.flow_runs
Process for flow run 'phenomenal-sidewinder' exited cleanly.
also, guess has nothing to do, but locally I have started (I cannot detect what has changed, not the code 99.9% sure) getting a different error 
ValueError: ctypes objects containing pointers cannot be pickled
UPDATE: Not sure why this was working earlier but I changed the logic to avoid returning custom class instances so we can ignore this.
@Kevin Grismore the only thing I can think of is that the k8s worker does not have the pandas dep installed, but unless I'm missing something this shouldn't be an issue?
k
what's installed on the worker has no relationship to what's going on in the pods where flow runs are happening
m
right
the ImagePullPolicy was set to 'IfNotPresent' in the default template, and there was something odd with the other image I tested this on... I'm setting it to 'Always' now which should be the de facto when using a ':latest' tag in k8s
Ok, now it's starting to get a little bit odd, this is the image, it has pandas installed:
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docker run -ti europe-docker.pkg.dev/cambium-earth/prefect-runners-staging/default:latest
WARNING: The requested image's platform (linux/amd64) does not match the detected host platform (linux/arm64/v8) and no specific platform was requested
  ___ ___ ___ ___ ___ ___ _____
 | _ \ _ \ __| __| __/ __|_   _|
 |  _/   / _|| _|| _| (__  | |
 |_| |_|_\___|_| |___\___| |_|


root@42107936d492:/opt/prefect# ls
dataflows	    dbt   entrypoint.sh		    requirements-client.txt  setup.py
dataflows.egg-info  dist  include-requirements.txt  requirements.txt
root@42107936d492:/opt/prefect# pip freeze
agate==1.9.1
aiohttp==3.9.5
aiosignal==1.3.1
aiosqlite==0.20.0
alembic==1.13.1
annotated-types==0.6.0
anyio==3.7.1
apprise==1.8.0
asgi-lifespan==2.1.0
async-timeout==4.0.3
asyncpg==0.29.0
attrs==23.2.0
Babel==2.15.0
cachetools==5.3.3
certifi==2024.2.2
cffi==1.16.0
charset-normalizer==3.3.2
click==8.1.7
click-plugins==1.1.1
cligj==0.7.2
cloudpickle==3.0.0
colorama==0.4.6
coolname==2.2.0
croniter==2.0.5
cryptography==42.0.7
daff==1.3.46
# Editable install with no version control (dataflows==0.1.0)
-e /opt/prefect
dateparser==1.2.0
dbt-adapters==1.2.1
dbt-common==1.1.0
dbt-core==1.8.0
dbt-extractor==0.5.1
dbt-semantic-interfaces==0.5.1
decorator==5.1.1
dnspython==2.6.1
docker==6.1.3
duckdb==0.10.2
email_validator==2.1.1
exceptiongroup==1.2.1
Faker==24.14.1
fiona==1.9.6
frozenlist==1.4.1
fsspec==2024.3.1
gcsfs==2024.3.1
geopandas==0.14.4
google-api-core==2.19.0
google-api-python-client==2.129.0
google-auth==2.29.0
google-auth-httplib2==0.2.0
google-auth-oauthlib==1.2.0
google-cloud-core==2.4.1
google-cloud-storage==2.16.0
google-crc32c==1.5.0
google-resumable-media==2.7.0
googleapis-common-protos==1.63.0
graphql-core==3.2.3
graphviz==0.20.3
greenlet==3.0.3
griffe==0.45.0
h11==0.14.0
h2==4.1.0
hpack==4.0.0
httpcore==1.0.5
httplib2==0.22.0
httpx==0.27.0
humanize==4.9.0
hyperframe==6.0.1
idna==3.7
importlib-metadata==6.11.0
importlib_resources==6.1.3
isodate==0.6.1
itsdangerous==2.2.0
Jinja2==3.1.4
jinja2-humanize-extension==0.4.0
jsonpatch==1.33
jsonpointer==2.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
kubernetes==29.0.0
leather==0.4.0
Logbook==1.5.3
Mako==1.3.5
Markdown==3.6
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mashumaro==3.13
mdurl==0.1.2
minimal-snowplow-tracker==0.0.2
more-itertools==10.2.0
msgpack==1.0.8
multidict==6.0.5
networkx==3.3
numpy==1.26.4
oauthlib==3.2.2
orjson==3.10.3
packaging==24.0
pandas==2.2.2
parsedatetime==2.6
pathspec==0.12.1
pendulum==2.1.2
prefect==2.18.1
prefect-dbt==0.4.3
prefect-gcp==0.5.10
prefect-shell==0.2.5
proto-plus==1.23.0
protobuf==4.25.3
psycopg==3.1.19
pyasn1==0.6.0
pyasn1_modules==0.4.0
pycparser==2.22
pydantic==2.7.1
pydantic_core==2.18.2
pygit2==1.14.1
Pygments==2.18.0
pyparsing==3.1.2
pyproj==3.6.1
python-dateutil==2.9.0.post0
python-dotenv==1.0.1
python-multipart==0.0.9
python-slugify==8.0.4
pytimeparse==1.1.8
pytz==2024.1
pytzdata==2020.1
PyYAML==6.0.1
readchar==4.1.0
referencing==0.35.1
regex==2024.5.15
requests==2.31.0
requests-oauthlib==2.0.0
rfc3339-validator==0.1.4
rich==13.7.1
rpds-py==0.18.1
rsa==4.9
ruamel.yaml==0.18.6
ruamel.yaml.clib==0.2.8
sgqlc==16.3
shapely==2.0.4
shellingham==1.5.4
six==1.16.0
sniffio==1.3.1
SQLAlchemy==2.0.30
sqlparse==0.5.0
tenacity==8.3.0
text-unidecode==1.3
toml==0.10.2
typer==0.12.3
typing_extensions==4.11.0
tzdata==2024.1
tzlocal==5.2
ujson==5.10.0
uritemplate==4.1.1
urllib3==2.2.1
uvicorn==0.28.1
websocket-client==1.8.0
websockets==12.0
yarl==1.9.4
zipp==3.18.2
The job's pod definition shows that the 
ImagePullPolicy
is correctly set to `'Always'`:
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k get pod -n prefect amigurumi-grebe-hmq8s-78mwz -o yaml

<...>
image: europe-docker.pkg.dev/cambium-earth/prefect-runners-staging/default:latest
    imagePullPolicy: Always
    name: prefect-job
    resources:
      limits:
        cpu: 1200m
        memory: 8Gi
      requests:
        cpu: 110m
        memory: 128Mi
<...>
And yet the same error occurs:
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Job 'amigurumi-grebe-hmq8s': Pod has status 'Running'.
09:46:08 AM
prefect.flow_runs.worker
Opening process...
09:46:10 AM
prefect.flow_runs.runner
Downloading flow code from storage at '.'
09:46:14 AM
prefect.flow_runs
Flow could not be retrieved from deployment.
Traceback (most recent call last):
  File "", line 940, in exec_module
  File "", line 241, in _call_with_frames_removed
  File "/opt/prefect/data-canopy/data-flows/dataflows/flows/projects_observability_export_flow.py", line 4, in 
    import pandas as pd
ModuleNotFoundError: No module named 'pandas'
Am I missing something obvious?
might this be related to https://github.com/PrefectHQ/prefect/issues/8337? I am currently working it around using
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"env": {
                "EXTRA_PIP_PACKAGES": "pandas==2.2.2 geopandas==0.14.4 psycopg==3.1.19 psycopg-binary==3.1.19",
            }
In my 
job_variables
cc @Kevin Grismore
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