If you run flower with Celery 5.0.0 or if you use the docker image, it will say it cannot import "Command".

Steps to reproduce the behavior:

1. pip install celery==5.0.0 THEN
2. flower --version OR
3. flower -A proj --broker=redis://redis OR
4. flower

The Command class is no longer part of the base module: https://docs.celeryproject.org/en/v5.0.0/reference/celery.bin.base.html

Which means it can no longer import and inherit Command:

from __future__ import absolute_import
from __future__ import print_function

import os
import sys
import atexit
import signal
import logging

from pprint import pformat

from logging import NullHandler

from tornado.options import options
from tornado.options import parse_command_line, parse_config_file
from tornado.log import enable_pretty_logging
from celery.bin.base import Command

from . import __version__
from .app import Flower
from .urls import settings
from .utils import abs_path, prepend_url
from .options import DEFAULT_CONFIG_FILE, default_options


logger = logging.getLogger(__name__)


class FlowerCommand(Command):
    # ...

Although using --url_prefix parameter does not give error when running Flower, but it doesn't work anymore. Also deprecated is written on this parameter in the latest source code. So does there exist an alternative to this parameter or from now on Flower can only be run on root?

Im trying to run flower on my local celery deployment. When I try to connect via web browser to localhost:5555 or via curl , it just hangs forever (waiting for localhost). I can telnet to port 5555, but other than that no response. Below is some debug info:

celery -A myproject flower --broker=redis://localhost:6379/0 --broker_api=redis://localhost:6379/0 --debug --inspect_timeout=10 [I 161120 20:08:01 command:136] Visit me at http://localhost:5555 [I 161120 20:08:01 command:141] Broker: redis://localhost:6379/0 [I 161120 20:08:01 command:144] Registered tasks: [u'app.tasks.generate_scheduled', u'celery.accumulate', u'celery.backend_cleanup', u'celery.chain', u'celery.chord', u'celery.chord_unlock', u'celery.chunks', u'celery.group', u'celery.map', u'celery.starmap', u'app.tasks.generate_result', 'normalize_time_task', u'myplatform.celery.debug_task', u'tasks.bake_block', 'tasks.baker', 'tasks.mailman'] [D 161120 20:08:01 command:146] Settings: {'cookie_secret': 'pnKuJkmuRPW43p1N4KYmvRAZjwFJtE+dvDWUNGrHTl8=', 'debug': True, 'login_url': '/login', 'static_path': '/usr/local/lib/python2.7/site-packages/flower-0.9.1-py2.7.egg/flower/static', 'static_url_prefix': '/static/', 'template_path': '/usr/local/lib/python2.7/site-packages/flower-0.9.1-py2.7.egg/flower/templates'} [D 161120 20:08:01 control:29] Updating all worker's cache... [I 161120 20:08:01 mixins:224] Connected to redis://localhost:6379/0

Celery 5 consists of a refactor to the CLI framework. The celery command and its sub-commands are now powered by Click. In version 5.0.5, the ability to extend the base command was restored, and so in order to invoke flower on Celery >=5, <5.0.5 using this change, you would have to:

flower -A app flower 

For the newest patch, it can be executed as any other celery subcommand:

celery -A app flower

This change probably requires a major version upgrade as it has major version dependency upgrade for celery.

Offline workers create a lot of noise in the flower dashboard when running Celery in a containerised environment like kubernetes. See also #840.

I've added a new option purge_offline_workers (--purge_offline_workers / FLOWER_PURGE_OFFLINE_WORKERS) that removes offline workers from the flower dashboard.

purge_offline_workers is optional and defaults to False so that it does not impact default behaviour.

On the Monitor tab, the graph is only displaying the traffic for my local (same server that runs rabbitMQ and flower) celery worker. It is not displaying the traffic for my remote (running on different server) celery worker.

I am sure I have started the remote worker correctly and have it configured correctly, because the other Flower tabs do show that the remote tasks are being executed successfully. And, my app is working fine.

Not sure if it is a factor or not, but each worker is assigned its own distinct queue. Also I should mention that the local worker task uses apply_async to send a task to the remote worker, in case this is unusual.

I'm new to python, Celery, and Flower. If you can offer suggestions on what I might be doing wrong, I'll sure appreciate it.

Thanks, Steve

Error appears in an alert dialog containing this text: DataTables warning: table id=tasks-table - Ajax error. For more information about this error, please see http://datatables.net/tn/7

Looks like Tornado dropped this decorator in the latest release v6.0.0b1.

When trying to run 'celery flower' last message in stack trace is;

AttributeError: module 'tornado.web' has no attribute 'asynchronous'

celery report software -> celery:3.1.13 (Cipater) kombu:3.0.21 py:3.4.0 billiard:3.3.0.18 py-amqp:1.4.5 platform -> system:Linux arch:64bit, ELF imp:CPython loader -> celery.loaders.default.Loader settings -> transport:amqp results:disabled

redis-server --version Redis server v=2.8.9 sha=00000000:0 malloc=jemalloc-3.2.0 bits=64 build=6183a7cf6dbec67f

pip list amqp (1.4.5) anyjson (0.3.3) billiard (3.3.0.18) celery (3.1.13) cement (2.2.2) certifi (14.05.14) flower (0.7.2) hiredis (0.1.4) humanize (0.5) kombu (3.0.21) msgpack-python (0.4.2) Pillow (2.5.1) pip (1.5.4) pycket (0.3.0) pymongo (2.7.2) pytz (2014.4) redis (2.10.1) requests (2.3.0) setuptools (2.1) tornado (4.0) WTForms (2.0.1) wtforms-tornado (0.0.1)

supervisord.conf [program:lusir-server-celery-worker-storage] command=celery worker -A celeryapp.celeryapp -l info -E -Q storage -I lusir.storage.task -n storage@%%n directory=%(ENV_HOME)s/projects/longyuan/lusir-server/src autostart=true autorestart=true startsecs=10 stopwaitsecs=30

[program:lusir-server-celery-worker-message] command=celery worker -A celeryapp.celeryapp -l info -E -Q message -I lusir.message.task -n message@%%n directory=%(ENV_HOME)s/projects/longyuan/lusir-server/src autostart=true autorestart=true startsecs=10 stopwaitsecs=30

[program:lusir-server-celery-worker-face] command=celery worker -A celeryapp.celeryapp -l info -E -Q face -I lusir.face.task -n face@%%n directory=%(ENV_HOME)s/projects/longyuan/lusir-server/src autostart=true autorestart=true startsecs=10 stopwaitsecs=30

[program:lusir-server-celery-worker-star] command=celery worker -A celeryapp.celeryapp -l info -E -Q star -I lusir.star.task -n star@%%n directory=%(ENV_HOME)s/projects/longyuan/lusir-server/src autostart=true autorestart=true startsecs=10 stopwaitsecs=30

[program:lusir-server-celery-flower] command=flower --address=0.0.0.0 --port=8110 --broker=redis://lusir-redis-test:6379/12 --broker_api=redis://lusir-redis-test:6379/12 --url_prefix=flower directory=%(ENV_HOME)s/projects/longyuan/lusir-server/src autostart=true autorestart=true startsecs=10 stopwaitsecs=30

This backward-compatible change introduces a new persistence mode that is more reliable for a long-running process.

With the shelve based persistence, data is written to disk only when cleanly stopping Flower. If for any reason the process is abnormally terminated, the in-memory data is lost. This unfortunately happens quite often when running Flower inside a Docker container.

Postgres persistence implemented here works by adding an event callback to the EventsState instance that inserts events into the database as they happen (excluding worker heartbeat events). On process start, these events are replayed to recreate the State instance as it was.

Note that migration of data persisted in shelf databases is not possible (or at least easy) -- as such a migration would need to recreate events based on aggregated state.

Please review and comment; if I this feature is to be accepted I will add documentation for it.

I am deploying Flower with Chef on a sentinel node.

I've been trying to start the flower service with path/to/bin/celery --broker=redis://brokerurl/0 --port=5555 flower

I can navigate to the Flower page just fine, but no tasks appear. When I go to the broker tab, no queues are listed.

What could be wrong? What else is needed?

The following metrics of flower do show on prometheus but aren't documented, I do not know what they represent.

flower_task_runtime_seconds_sum
flower_task_runtime_seconds_count

this expression rate(flower_task_runtime_seconds_sum[5m]) / rate(flower_task_runtime_seconds_count[5m]) is used on example dashboard in this repo but not documentation is provided.

Describe the bug Unable to start flower when redis is protected by password

$celery --broker=redis://:$REDIS_PASSWORD@localhost:6379/0 flower

System information Traceback (most recent call last): File "/venv/lib/python3.8/site-packages/kombu/connection.py", line 446, in _reraise_as_library_errors yield File "/venv/lib/python3.8/site-packages/kombu/connection.py", line 433, in _ensure_connection return retry_over_time( File "/venv/lib/python3.8/site-packages/kombu/utils/functional.py", line 312, in retry_over_time return fun(*args, **kwargs) File "/venv/lib/python3.8/site-packages/kombu/connection.py", line 877, in _connection_factory self._connection = self._establish_connection() File "/venv/lib/python3.8/site-packages/kombu/connection.py", line 812, in _establish_connection conn = self.transport.establish_connection() File "/venv/lib/python3.8/site-packages/kombu/transport/virtual/base.py", line 949, in establish_connection self._avail_channels.append(self.create_channel(self)) File "/venv/lib/python3.8/site-packages/kombu/transport/virtual/base.py", line 927, in create_channel channel = self.Channel(connection) File "/venv/lib/python3.8/site-packages/kombu/transport/redis.py", line 737, in init self.client.ping() File "/venv/lib/python3.8/site-packages/redis/commands/core.py", line 1132, in ping return self.execute_command("PING", **kwargs) File "/venv/lib/python3.8/site-packages/redis/client.py", line 1235, in execute_command conn = self.connection or pool.get_connection(command_name, **options) File "/venv/lib/python3.8/site-packages/redis/connection.py", line 1387, in get_connection connection.connect() File "/venv/lib/python3.8/site-packages/redis/connection.py", line 623, in connect self.on_connect() File "/venv/lib/python3.8/site-packages/redis/connection.py", line 713, in on_connect auth_response = self.read_response() File "/venv/lib/python3.8/site-packages/redis/connection.py", line 839, in read_response raise response redis.exceptions.ResponseError: AUTH called without any password configured for the default user. Are you sure your configuration is correct?

The above exception was the direct cause of the following exception

Describe the bug

My flower is up and running. Nevertheless, my Sentry instance is collecting those exceptions from time to time. I'd like to keep my Sentry clean and tidy and therefore like to find a solution to avoid those errors.

To Reproduce

Command:

celery -A apps.config.celery_settings flower --port=5555 --basic_auth=my_user:my_password

Install flower and wait for some time 😞

Actually, I don't use the Google feature that is apparently causing the error.

Expected behavior

We don't get these exceptions or can disable them.

Screenshots

I am using flower v1.2.0.

As a downstream user it is desirable to be able to programmatically determine the precise licenses used by our dependencies. The emerging convention for this is the SPDX License List. SPDX License Expressions are already used in the JavaScript (npm) and Rust (crates.io) ecosystems, for example.

In Python, there is PEP 639 which would add a standard 'License-Expression' metadata field. The discussion around this PEP seems to have gone stale in 2021.

This merge request is in lieu of that PEP coming soon. Unless you as project maintainers think the proposed change in this PR has downsides (which you are entitled to!), I would ask that you accept this change so that it's possible for users to attempt to parse your license metadata as an SPDX License Expression. In particular, BSD is ambiguous as there are multiple BSD licenses.

If PEP 639 is accepted, this package would be ready for the change just by changing the license key to license-expression or whatever key the PEP lands on.

I could set max_tasks to a much smaller number if this was possible, thus wasting less memory / database space storing successful tasks that I'm not interested in.

(If this is already possible, please enlighten me - I looked through the docs and didn't find anything.)