Trans article #28
Trans article #28
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Caution Review failedThe pull request is closed. WalkthroughCelery integration was added to the Django backend. This involved updating dependencies, creating and configuring a Celery app with signal handlers for logging, defining and scheduling a sample task, and adding Celery-related settings to production and testing configurations. The Celery app import and export are now conditional based on task execution mode. Changes
Sequence Diagram(s)sequenceDiagram
participant Django
participant CeleryApp
participant Logfire
participant Worker
participant Beat
Django->>CeleryApp: Import celery_app if CELERY_ALWAYS_EAGER is False
CeleryApp->>CeleryApp: Load config from Django settings (CELERY_ prefix)
CeleryApp->>CeleryApp: Discover tasks from installed apps
Worker->>CeleryApp: worker_init signal
CeleryApp->>Logfire: Configure logfire (service_name="celery-worker", enable celery instrumentation)
Beat->>CeleryApp: beat_init signal
CeleryApp->>Logfire: Configure logfire (service_name="celery-beat", enable celery instrumentation)
CeleryApp->>CeleryApp: Schedule add task every 30s
CeleryApp->>Worker: Send add(16, 16) task (periodic)
CeleryApp->>Worker: Send add(42, 50) task (on startup)
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Actionable comments posted: 5
🧹 Nitpick comments (4)
pythonkr_backend/pythonkr_backend/__init__.py (1)
1-5: LGTM! Consider minor formatting improvements.The Celery app import and exposure is correctly implemented for Django integration. The comments clearly explain the purpose.
Apply this diff to address static analysis concerns:
+"""Django package initialization with Celery integration.""" # This will make sure the app is always imported when # Django starts so that shared_task will use this app. from .celery import app as celery_app -__all__ = ('celery_app',) +__all__ = ('celery_app',)🧰 Tools
🪛 Pylint (3.3.7)
[convention] 5-5: Final newline missing
(C0304)
[convention] 1-1: Missing module docstring
(C0114)
pythonkr_backend/pythonkr_backend/settings/prod.py (1)
71-79: Fix formatting issues.Address trailing whitespace and missing final newline.
-# celery +# celery CELERY_BROKER_PASSWORD = os.environ.get("CELERY_PASSWORD","FALSE") CELERY_BROKER_USERNAME = os.environ.get("CELERY_USERNAME","FALSE") CELERY_BROKER_VHOST = os.environ.get("CELERY_VHOST","FALSE") # Celery Configuration Options CELERY_TIMEZONE = "Asia/Seoul" CELERY_TASK_TRACK_STARTED = True CELERY_BROKER_URL = "amqp://userid:password@localhost:port/virtual_host" -CELERY_TASK_TIME_LIMIT = 30 * 60 +CELERY_TASK_TIME_LIMIT = 30 * 60🧰 Tools
🪛 Pylint (3.3.7)
[convention] 71-71: Trailing whitespace
(C0303)
[convention] 79-79: Final newline missing
(C0304)
pythonkr_backend/pythonkr_backend/celery.py (2)
5-5: Consider using a more descriptive app name.The app name 'proj' is too generic. Consider using the actual project name.
-app = Celery('proj') +app = Celery('pythonkr_backend')
1-41: Add module docstring and fix formatting issues.Address the missing module docstring and trailing whitespace issues.
+""" +Celery application configuration for Django integration. + +This module sets up the Celery app instance, configures it to work with Django, +and defines signal handlers for logging instrumentation. +""" import logfire from celery import Celery from celery.signals import worker_init, beat_init🧰 Tools
🪛 Pylint (3.3.7)
[convention] 18-18: Trailing whitespace
(C0303)
[convention] 20-20: Trailing whitespace
(C0303)
[convention] 23-23: Trailing whitespace
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[convention] 25-25: Trailing whitespace
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[convention] 35-35: Trailing whitespace
(C0303)
[convention] 41-41: Final newline missing
(C0304)
[convention] 1-1: Missing module docstring
(C0114)
[error] 1-1: Unable to import 'logfire'
(E0401)
[error] 2-2: Unable to import 'celery'
(E0401)
[error] 3-3: Unable to import 'celery.signals'
(E0401)
[convention] 19-19: Missing function or method docstring
(C0116)
[warning] 19-19: Unused argument 'args'
(W0613)
[warning] 19-19: Unused argument 'kwargs'
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[convention] 24-24: Missing function or method docstring
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[warning] 24-24: Unused argument 'args'
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[warning] 24-24: Unused argument 'kwargs'
(W0613)
[convention] 29-29: Missing function or method docstring
(C0116)
🪛 GitHub Actions: pk web site backend testing
[error] 32-32: Celery task 'add.delay(42, 50)' failed due to kombu.exceptions.OperationalError: [Errno 111] Connection refused. The AMQP connection to the message broker could not be established.
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📒 Files selected for processing (4)
pyproject.toml(1 hunks)pythonkr_backend/pythonkr_backend/__init__.py(1 hunks)pythonkr_backend/pythonkr_backend/celery.py(1 hunks)pythonkr_backend/pythonkr_backend/settings/prod.py(1 hunks)
🧰 Additional context used
🪛 Pylint (3.3.7)
pythonkr_backend/pythonkr_backend/__init__.py
[convention] 5-5: Final newline missing
(C0304)
[convention] 1-1: Missing module docstring
(C0114)
pythonkr_backend/pythonkr_backend/celery.py
[convention] 18-18: Trailing whitespace
(C0303)
[convention] 20-20: Trailing whitespace
(C0303)
[convention] 23-23: Trailing whitespace
(C0303)
[convention] 25-25: Trailing whitespace
(C0303)
[convention] 35-35: Trailing whitespace
(C0303)
[convention] 41-41: Final newline missing
(C0304)
[convention] 1-1: Missing module docstring
(C0114)
[error] 1-1: Unable to import 'logfire'
(E0401)
[error] 2-2: Unable to import 'celery'
(E0401)
[error] 3-3: Unable to import 'celery.signals'
(E0401)
[convention] 19-19: Missing function or method docstring
(C0116)
[warning] 19-19: Unused argument 'args'
(W0613)
[warning] 19-19: Unused argument 'kwargs'
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[convention] 24-24: Missing function or method docstring
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[warning] 24-24: Unused argument 'args'
(W0613)
[warning] 24-24: Unused argument 'kwargs'
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[convention] 29-29: Missing function or method docstring
(C0116)
pythonkr_backend/pythonkr_backend/settings/prod.py
[convention] 71-71: Trailing whitespace
(C0303)
[convention] 79-79: Final newline missing
(C0304)
🪛 GitHub Actions: pk web site backend testing
pythonkr_backend/pythonkr_backend/celery.py
[error] 32-32: Celery task 'add.delay(42, 50)' failed due to kombu.exceptions.OperationalError: [Errno 111] Connection refused. The AMQP connection to the message broker could not be established.
🔇 Additional comments (4)
pyproject.toml (2)
16-16: LGTM! Logfire Celery integration properly configured.Adding
celeryto the logfire extras is correct for instrumenting Celery tasks.
9-9:✅ Verification successful
Verify Celery version for security and compatibility.
The addition of
celery>=5.5.2is appropriate for the integration.
🌐 Web query:
What is the latest stable version of Celery and are there any known security vulnerabilities in version 5.5.2?💡 Result:
Latest Stable Version of Celery
The latest stable version of Celery as of June 2025 is 5.5.2[1][2]. This version was released on April 25, 2025 and includes several bug fixes and improvements, particularly around time calculations and documentation updates[2].
Security Vulnerabilities in Celery 5.5.2
There are no known security vulnerabilities reported in Celery version 5.5.2. Multiple reputable sources confirm this:
- ReversingLabs Spectra Assure has scanned Celery 5.5.2 and states clearly: “No known vulnerabilities detected,” with no issues found for compliance, secrets, security, or malware[6].
- Snyk Security’s vulnerability database lists no direct vulnerabilities for version 5.5.2 of Celery[9]. The previous vulnerabilities affected much earlier versions and do not apply to 5.5.2.
Additional Security Context and Best Practices
While earlier versions of Celery have experienced vulnerabilities like insecure deserialization and risks around unencrypted communications, there is no indication that these issues remain in 5.5.2[7]. To maintain security, it is recommended to:
- Regularly audit your configurations and dependencies.
- Use secure communication protocols (e.g., TLS/SSL).
- Follow secure coding practices and monitor for new advisories.
Summary Table
Celery Version Release Date Known Security Vulns 5.5.2 2025-04-25 None reported Celery 5.5.2 is the current stable release, and no security vulnerabilities are known for this version as of June 2025[1][2][6][9].
Citations:
- 1: https://pypi.org/project/celery/
- 2: https://github.com/celery/celery/releases
- 3: https://support.celerypayroll.com/en/support/solutions/folders/6000244400
- 4: https://moldstud.com/articles/p-celery-release-cycle-key-dates-and-expected-features-for-2025
- 5: https://readthedocs.org/projects/celery/
- 6: https://secure.software/pypi/packages/celery/5.5.2
- 7: https://moldstud.com/articles/p-are-there-any-known-security-vulnerabilities-in-celery
- 8: https://docs.celeryproject.org/en/latest/getting-started/introduction.html
- 9: https://security.snyk.io/package/pip/celery
- 10: https://security.snyk.io/package/pip/celery/5.5.0b1
Approve Celery 5.5.2 in pyproject.toml
- pyproject.toml (line 9):
celery>=5.5.2Celery 5.5.2 is the latest stable release (Apr 25, 2025) and has no known security vulnerabilities as of June 2025. No further changes required.
pythonkr_backend/pythonkr_backend/settings/prod.py (1)
72-74: Environment variable configuration looks good.Using environment variables for broker credentials is a good security practice.
pythonkr_backend/pythonkr_backend/celery.py (1)
12-15: LGTM! Django configuration integration is correct.The configuration loading and task autodiscovery are properly implemented.
| "lxml>=5.3.2", | ||
| "markdown>=3.7", | ||
| "psycopg[binary]>=3.2.5", | ||
| "pydantic-ai-slim[anthropic,openai]>=0.2.6", |
There was a problem hiding this comment.
💡 Verification agent
🧩 Analysis chain
Verify AI package versions and compatibility.
The addition of pydantic-ai-slim[anthropic,openai]>=0.2.6 looks appropriate for AI functionality.
🌐 Web query:
What is the latest version of pydantic-ai-slim and are there any compatibility issues with the specified extras?
💡 Result:
The latest version of pydantic-ai-slim is 0.2.12, released on May 29, 2025[1]. This package serves as an agent framework/shim to use Pydantic with large language models (LLMs), offering a slimmer version with minimal required dependencies.
Optional Extras
Pydantic-ai-slim provides several optional dependency groups that can be installed based on your specific needs:
logfire— installs thelogfirePyPI packageevals— installs thepydantic-evalsPyPI packageopenai— installs theopenaiPyPI packagevertexai— installsgoogle-authandrequestsPyPI packagesanthropic— installs theanthropicPyPI packagegroq— installs thegroqPyPI packagemistral— installs themistralaiPyPI packagecohere— installs thecoherePyPI packageduckduckgo— installs theduckduckgo-searchPyPI packagetavily— installs thetavily-pythonPyPI package[2]
You can install multiple extras simultaneously using the syntax:
pip install "pydantic-ai-slim[openai,vertexai,logfire]"
or
uv add "pydantic-ai-slim[openai,vertexai,logfire]"
```[2]
## Compatibility Issues
There have been some compatibility issues noted:
1. **Databricks ML Runtime**: There's an incompatibility with Databricks' ML runtime 16.3ML. The issue relates to dependency conflicts, particularly with the `requests` package. Pydantic-ai requires `requests (>=2.32.3)`, but Databricks ML runtime uses version 2.32.2, causing version solving to fail[7].
2. **AWS Lambda Deployment**: When deploying applications with pydantic packages to AWS Lambda, especially using frameworks like serverless, there can be issues with package metadata. The `slim` setting in serverless deployment configuration might need to be set to `false` to ensure proper inclusion of metadata for dependencies[6].
3. **Breaking Changes**: While not specific to the slim package, the parent project pydantic-ai has undergone breaking changes in recent versions. In v0.2.0 (May 12, 2025), there were changes to the `usage` field in `ModelResponse` and modifications to the return type of `Model.request`[4].
For the most up-to-date information on compatibility and how to use specific models with the required dependencies, it's recommended to check the models documentation mentioned in the installation guide[2].
Citations:
- 1: https://pypi.org/project/pydantic-ai-slim/
- 2: https://ai.pydantic.dev/install/
- 3: https://github.com/pydantic/pydantic-ai/releases
- 4: https://ai.pydantic.dev/changelog/
- 5: https://pypistats.org/packages/pydantic-ai
- 6: https://docs.pydantic.dev/latest/integrations/aws_lambda/
- 7: https://github.com/pydantic/pydantic-ai/issues/1582
- 8: https://www.piwheels.org/project/pydantic-ai-slim/
- 9: https://www.youtube.com/watch?v=ferNt5JTaGQ
- 10: https://docs.pydantic.dev/2.3/version-compatibility/
---
</details>
**Pin pydantic-ai-slim to the latest release and verify compatibility**
- In pyproject.toml (line 20), bump the requirement:
```diff
- "pydantic-ai-slim[anthropic,openai]>=0.2.6",
+ "pydantic-ai-slim[anthropic,openai]>=0.2.12",
- Confirm that the
anthropicandopenaiextras cover all needed LLM providers. - Be aware of known compatibility issues:
• Databricks ML Runtime 16.3ML shipsrequests==2.32.2(pydantic-ai-slim needs ≥2.32.3).
• AWS Lambda/serverless may requireslim: falseto include package metadata. - Ensure no regressions from parent pydantic-ai’s breaking changes (v0.2.0) around
ModelResponse.usageandModel.requestreturn types.
📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| "pydantic-ai-slim[anthropic,openai]>=0.2.6", | |
| "pydantic-ai-slim[anthropic,openai]>=0.2.12", |
🤖 Prompt for AI Agents
In pyproject.toml at line 20, update the pydantic-ai-slim dependency version
from ">=0.2.6" to the latest stable release ">=0.2.12". Verify that the included
extras "anthropic" and "openai" sufficiently cover all required LLM providers
for your project. Additionally, review and address any compatibility issues such
as the Databricks ML Runtime requests version conflict and AWS Lambda deployment
metadata inclusion by adjusting serverless settings if needed. Finally, test to
ensure no regressions occur due to breaking changes in pydantic-ai v0.2.0
related to ModelResponse.usage and Model.request return types.
| CELERY_TASK_TRACK_STARTED = True | ||
| CELERY_BROKER_URL = "amqp://userid:password@localhost:port/virtual_host" | ||
| CELERY_TASK_TIME_LIMIT = 30 * 60 |
There was a problem hiding this comment.
Critical: Fix hardcoded broker URL with placeholder values.
The hardcoded broker URL contains placeholder values that will cause connection failures, as evidenced by the pipeline error.
Apply this diff to use the environment variables properly:
-CELERY_BROKER_URL = "amqp://userid:password@localhost:port/virtual_host"
+CELERY_BROKER_URL = f"amqp://{CELERY_BROKER_USERNAME}:{CELERY_BROKER_PASSWORD}@localhost:5672/{CELERY_BROKER_VHOST}"Additionally, consider adding validation for the environment variables:
+# Validate required Celery environment variables
+if CELERY_BROKER_USERNAME == "FALSE" or CELERY_BROKER_PASSWORD == "FALSE" or CELERY_BROKER_VHOST == "FALSE":
+ raise ValueError("Celery broker credentials must be properly configured via environment variables")📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| CELERY_TIMEZONE = "Asia/Seoul" | |
| CELERY_TASK_TRACK_STARTED = True | |
| CELERY_BROKER_URL = "amqp://userid:password@localhost:port/virtual_host" | |
| CELERY_TASK_TIME_LIMIT = 30 * 60 | |
| CELERY_TIMEZONE = "Asia/Seoul" | |
| CELERY_TASK_TRACK_STARTED = True | |
| # Validate required Celery environment variables | |
| if CELERY_BROKER_USERNAME == "FALSE" or CELERY_BROKER_PASSWORD == "FALSE" or CELERY_BROKER_VHOST == "FALSE": | |
| raise ValueError("Celery broker credentials must be properly configured via environment variables") | |
| CELERY_BROKER_URL = f"amqp://{CELERY_BROKER_USERNAME}:{CELERY_BROKER_PASSWORD}@localhost:5672/{CELERY_BROKER_VHOST}" | |
| CELERY_TASK_TIME_LIMIT = 30 * 60 |
🧰 Tools
🪛 Pylint (3.3.7)
[convention] 79-79: Final newline missing
(C0304)
🤖 Prompt for AI Agents
In pythonkr_backend/pythonkr_backend/settings/prod.py around lines 76 to 79, the
CELERY_BROKER_URL is hardcoded with placeholder values that will cause
connection failures. Replace the hardcoded string with a construction that reads
the broker URL components (userid, password, host, port, virtual_host) from
environment variables using os.environ.get or a similar method. Also, add
validation to check that these environment variables are set and raise an error
or log a clear message if any are missing to prevent silent failures.
| @app.task | ||
| def add(x: int, y: int): | ||
| return x + y | ||
|
|
||
| add.delay(42, 50) |
There was a problem hiding this comment.
Critical: Remove task execution at module level.
Executing the task at module import time will cause connection errors during Django startup, as evidenced by the pipeline failure.
@app.task
def add(x: int, y: int):
+ """Add two integers and return the result."""
return x + y
-add.delay(42, 50)If you need to test the task, consider adding it to a management command or view instead.
📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| @app.task | |
| def add(x: int, y: int): | |
| return x + y | |
| add.delay(42, 50) | |
| @app.task | |
| def add(x: int, y: int): | |
| """Add two integers and return the result.""" | |
| return x + y |
🧰 Tools
🪛 Pylint (3.3.7)
[convention] 29-29: Missing function or method docstring
(C0116)
🪛 GitHub Actions: pk web site backend testing
[error] 32-32: Celery task 'add.delay(42, 50)' failed due to kombu.exceptions.OperationalError: [Errno 111] Connection refused. The AMQP connection to the message broker could not be established.
🤖 Prompt for AI Agents
In pythonkr_backend/pythonkr_backend/celery.py around lines 28 to 32, the task
add.delay(42, 50) is being executed at the module level, which causes connection
errors during Django startup. Remove the add.delay(42, 50) call from the module
to prevent this. If you want to test the task, move the call to a Django
management command or a view where it can be triggered explicitly.
| @worker_init.connect() | ||
| def init_worker(*args, **kwargs): | ||
| logfire.configure(service_name="celery-worker") | ||
| logfire.instrument_celery() | ||
|
|
||
| @beat_init.connect() | ||
| def init_beat(*args, **kwargs): | ||
| logfire.configure(service_name="celery-beat") | ||
| logfire.instrument_celery() |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Improve signal handler implementation.
The signal handlers have unused arguments and missing docstrings.
-@worker_init.connect()
-def init_worker(*args, **kwargs):
- logfire.configure(service_name="celery-worker")
+@worker_init.connect()
+def init_worker(*_args, **_kwargs):
+ """Initialize logfire instrumentation for Celery worker."""
+ logfire.configure(service_name="celery-worker")
logfire.instrument_celery()
-@beat_init.connect()
-def init_beat(*args, **kwargs):
- logfire.configure(service_name="celery-beat")
+@beat_init.connect()
+def init_beat(*_args, **_kwargs):
+ """Initialize logfire instrumentation for Celery beat scheduler."""
+ logfire.configure(service_name="celery-beat")
logfire.instrument_celery()📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| @worker_init.connect() | |
| def init_worker(*args, **kwargs): | |
| logfire.configure(service_name="celery-worker") | |
| logfire.instrument_celery() | |
| @beat_init.connect() | |
| def init_beat(*args, **kwargs): | |
| logfire.configure(service_name="celery-beat") | |
| logfire.instrument_celery() | |
| @worker_init.connect() | |
| def init_worker(*_args, **_kwargs): | |
| """Initialize logfire instrumentation for Celery worker.""" | |
| logfire.configure(service_name="celery-worker") | |
| logfire.instrument_celery() | |
| @beat_init.connect() | |
| def init_beat(*_args, **_kwargs): | |
| """Initialize logfire instrumentation for Celery beat scheduler.""" | |
| logfire.configure(service_name="celery-beat") | |
| logfire.instrument_celery() |
🧰 Tools
🪛 Pylint (3.3.7)
[convention] 18-18: Trailing whitespace
(C0303)
[convention] 20-20: Trailing whitespace
(C0303)
[convention] 23-23: Trailing whitespace
(C0303)
[convention] 25-25: Trailing whitespace
(C0303)
[convention] 19-19: Missing function or method docstring
(C0116)
[warning] 19-19: Unused argument 'args'
(W0613)
[warning] 19-19: Unused argument 'kwargs'
(W0613)
[convention] 24-24: Missing function or method docstring
(C0116)
[warning] 24-24: Unused argument 'args'
(W0613)
[warning] 24-24: Unused argument 'kwargs'
(W0613)
🤖 Prompt for AI Agents
In pythonkr_backend/pythonkr_backend/celery.py around lines 18 to 26, the signal
handler functions init_worker and init_beat have unused *args and **kwargs
parameters and lack docstrings. Remove the unused parameters from both functions
and add concise docstrings explaining their purpose as signal handlers for
worker and beat initialization respectively.
| app.conf.beat_schedule = { | ||
| "add-every-30-seconds": { | ||
| "task": "tasks.add", | ||
| "schedule": 30.0, | ||
| "args": (16, 16), | ||
| }, | ||
| } |
There was a problem hiding this comment.
💡 Verification agent
🧩 Analysis chain
Fix beat schedule task reference.
The task reference is incorrect and will cause the scheduled task to fail.
-app.conf.beat_schedule = {
+app.conf.beat_schedule = {
"add-every-30-seconds": {
- "task": "tasks.add",
+ "task": "pythonkr_backend.celery.add",
"schedule": 30.0,
"args": (16, 16),
},
}🏁 Script executed:
#!/bin/bash
# Verify the correct task path for the beat schedule
# Description: Check if there are other task definitions that might affect the correct path
ast-grep --pattern '@$_.task
def $_($_) {
$$$
}'Length of output: 52
To determine the correct import path for your Celery task, let’s locate where add is defined and how it’s decorated:
🏁 Script executed:
#!/bin/bash
# Find all Celery task definitions and look for `add`
rg -n -E '@(app\.task|shared_task)' --glob '*.py' -C3
rg -n 'def add' --glob '*.py' -C3Length of output: 921
Update beat_schedule to use the fully qualified task name
The beat_schedule entry currently points at "tasks.add", but your @app.task def add is defined in pythonkr_backend/pythonkr_backend/celery.py, so Celery expects the module path pythonkr_backend.celery.add.
• File: pythonkr_backend/pythonkr_backend/celery.py
Lines: 35–41
-app.conf.beat_schedule = {
- "add-every-30-seconds": {
- "task": "tasks.add",
- "schedule": 30.0,
- "args": (16, 16),
- },
-}
+app.conf.beat_schedule = {
+ "add-every-30-seconds": {
+ "task": "pythonkr_backend.celery.add",
+ "schedule": 30.0,
+ "args": (16, 16),
+ },
+}📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| app.conf.beat_schedule = { | |
| "add-every-30-seconds": { | |
| "task": "tasks.add", | |
| "schedule": 30.0, | |
| "args": (16, 16), | |
| }, | |
| } | |
| app.conf.beat_schedule = { | |
| "add-every-30-seconds": { | |
| "task": "pythonkr_backend.celery.add", | |
| "schedule": 30.0, | |
| "args": (16, 16), | |
| }, | |
| } |
🧰 Tools
🪛 Pylint (3.3.7)
[convention] 35-35: Trailing whitespace
(C0303)
[convention] 41-41: Final newline missing
(C0304)
🤖 Prompt for AI Agents
In pythonkr_backend/pythonkr_backend/celery.py around lines 35 to 41, the
beat_schedule task reference "tasks.add" is incorrect and will cause the
scheduled task to fail. Update the "task" value to the fully qualified module
path where the add task is defined, which is "pythonkr_backend.celery.add". This
ensures Celery can locate and execute the task correctly.
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