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Current behavior

I wanted to spend a little time contributing this weekend, so I ran pylint over this repo. I see this project has a .pylintrc but it looks like pylint isn't run in CI, so some things do show up.

I found one class of warning from pylint that I think is worth addressing: explicitly re-raising exceptions in try-catches with from.

The newest version of pylint added a check for this. You can see details in "Explicit Exception Chaining". That PEP describes a way to improve stack traces from try-catched exceptions.

without from

try:
    {}["a"]
except KeyError:
    raise RuntimeError("hey this does not exist")

Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
KeyError: 'a'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 4, in <module>
RuntimeError: hey this does not exist

with from

try:
    {}["a"]
except KeyError  as err:
    raise RuntimeError("hey this does not exist") from err

Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
KeyError: 'a'

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

Traceback (most recent call last):
  File "<stdin>", line 4, in <module>
RuntimeError: hey this does not exist

I think this language of "was the direct cause of the following exception" is clearer, and helps you to understand exactly where things started going wrong.

Proposed behavior

Would you be open to a pull request that changes try-catched exceptions in prefect to use this pattern? I wanted to ask first because right now there are 1334 places where that happens so it would touch a lot of code.

you can see them all like this:

pylint src/prefect/ | grep raise-missing-from > pylint.txt

I think this change would improve prefect and help save users some debugging time. Especially users who are not very experienced in Python.

Thanks for your time and consideration.

Notes for Hacktoberfest Contributors

This issue has been left open for Hacktoberfest 2020 contributors. If that describes you, welcome!

1. Leave a comment below claiming a sub-module
2. Identify all cases of this issue in that submodule by running code like the following in a terminal:

   pylint src/prefect/engine/cloud | grep "raise-missing-from"
   

3. Fix all of these cases.
   • see #3320 for an example
4. Open a pull request, following the steps in https://github.com/PrefectHQ/prefect/pulls
   • if there is already a changes/issue3306.yaml, add your name to the list of contributors
   • if there is not already a changes/issue3306.yaml, create one in your pull request, like in #3320

sub-modules with this problem

• ~src/prefect/client~ - @jameslamb (#3320)
• ~src/prefect/core~ - @brainless (#3383)
• ~src/prefect/engine~ - @brainless (#3383)
• src/prefect/environments/execution/dask
• src/prefect/environments/execution/k8s
• ~src/prefect/environments/storage~ - @shalika10
• src/prefect/tasks/airtable
• ~src/prefect/tasks/aws~ - @heyitskevin
• src/prefect/tasks/azure
• src/prefect/tasks/azureml
• ~src/prefect/tasks/databricks~ - @rikturr (#3448)
• src/prefect/tasks/dbt
• src/prefect/tasks/dropbox
• ~src/prefect/tasks/gcp~ - @ericlundy87 (#3326)
• src/prefect/tasks/great_expectations
• src/prefect/tasks/gsheets
• src/prefect/tasks/kubernetes
• ~src/prefect/tasks/mysql~ - @luthrap (#3428)
• ~src/prefect/tasks/postgres~ - @brunocasarotti
• src/prefect/tasks/redis
• src/prefect/tasks/rss
• src/prefect/tasks/snowflake
• ~src/prefect/tasks/spacy~ - @sp1thas
• src/prefect/tasks/template
• src/prefect/tasks/twitter
• ~src/prefect/utilities~ - @gabrielcalderon (#3429)

NOTE: This issue is not urgent. It's ok to claim a sub-module now and not contribute until Hacktoberfest begins on October 1st.

Description

The docker agent deployed locally on the same machine as the docker server fails to run tasks, they get stuck in the submitted state on the server. From the logs, it seems to relate to an inability to connect to host.docker.internal.

[2021-09-13 15:59:17,700] INFO - agent | Deploying flow run 2d52c82a-e890-4f66-a845-7f5b0664ef0d to execution environment...
[2021-09-13 15:59:18,038] INFO - agent | Completed deployment of flow run 2d52c82a-e890-4f66-a845-7f5b0664ef0d
Traceback (most recent call last):
  File "/usr/local/lib/python3.8/site-packages/urllib3/connection.py", line 169, in _new_conn
    conn = connection.create_connection(
  File "/usr/local/lib/python3.8/site-packages/urllib3/util/connection.py", line 96, in create_connection
    raise err
  File "/usr/local/lib/python3.8/site-packages/urllib3/util/connection.py", line 86, in create_connection
    sock.connect(sa)
ConnectionRefusedError: [Errno 111] Connection refused

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/local/lib/python3.8/site-packages/urllib3/connectionpool.py", line 699, in urlopen
    httplib_response = self._make_request(
  File "/usr/local/lib/python3.8/site-packages/urllib3/connectionpool.py", line 394, in _make_request
    conn.request(method, url, **httplib_request_kw)
  File "/usr/local/lib/python3.8/site-packages/urllib3/connection.py", line 234, in request
    super(HTTPConnection, self).request(method, url, body=body, headers=headers)
  File "/usr/local/lib/python3.8/http/client.py", line 1256, in request
    self._send_request(method, url, body, headers, encode_chunked)
  File "/usr/local/lib/python3.8/http/client.py", line 1302, in _send_request
    self.endheaders(body, encode_chunked=encode_chunked)
  File "/usr/local/lib/python3.8/http/client.py", line 1251, in endheaders
    self._send_output(message_body, encode_chunked=encode_chunked)
  File "/usr/local/lib/python3.8/http/client.py", line 1011, in _send_output
    self.send(msg)
  File "/usr/local/lib/python3.8/http/client.py", line 951, in send
    self.connect()
  File "/usr/local/lib/python3.8/site-packages/urllib3/connection.py", line 200, in connect
    conn = self._new_conn()
  File "/usr/local/lib/python3.8/site-packages/urllib3/connection.py", line 181, in _new_conn
    raise NewConnectionError(
urllib3.exceptions.NewConnectionError: <urllib3.connection.HTTPConnection object at 0x7f25672ab070>: Failed to establish a new connection: [Errno 111] Connection refused

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/local/lib/python3.8/site-packages/requests/adapters.py", line 439, in send
    resp = conn.urlopen(
  File "/usr/local/lib/python3.8/site-packages/urllib3/connectionpool.py", line 755, in urlopen
    retries = retries.increment(
  File "/usr/local/lib/python3.8/site-packages/urllib3/util/retry.py", line 574, in increment
    raise MaxRetryError(_pool, url, error or ResponseError(cause))
urllib3.exceptions.MaxRetryError: HTTPConnectionPool(host='host.docker.internal', port=4200): Max retries exceeded with url: / (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f25672ab070>: Failed to establish a new connection: [Errno 111] Connection refused'))

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/local/bin/prefect", line 8, in <module>
    sys.exit(cli())
  File "/usr/local/lib/python3.8/site-packages/click/core.py", line 829, in __call__
    return self.main(*args, **kwargs)
  File "/usr/local/lib/python3.8/site-packages/click/core.py", line 782, in main
    rv = self.invoke(ctx)
  File "/usr/local/lib/python3.8/site-packages/click/core.py", line 1259, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File "/usr/local/lib/python3.8/site-packages/click/core.py", line 1259, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File "/usr/local/lib/python3.8/site-packages/click/core.py", line 1066, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/usr/local/lib/python3.8/site-packages/click/core.py", line 610, in invoke
    return callback(*args, **kwargs)
  File "/usr/local/lib/python3.8/site-packages/prefect/cli/execute.py", line 53, in flow_run
    result = client.graphql(query)
  File "/usr/local/lib/python3.8/site-packages/prefect/client/client.py", line 548, in graphql
    result = self.post(
  File "/usr/local/lib/python3.8/site-packages/prefect/client/client.py", line 451, in post
    response = self._request(
  File "/usr/local/lib/python3.8/site-packages/prefect/client/client.py", line 737, in _request
    response = self._send_request(
  File "/usr/local/lib/python3.8/site-packages/prefect/client/client.py", line 602, in _send_request
    response = session.post(
  File "/usr/local/lib/python3.8/site-packages/requests/sessions.py", line 590, in post
    return self.request('POST', url, data=data, json=json, **kwargs)
  File "/usr/local/lib/python3.8/site-packages/requests/sessions.py", line 542, in request
    resp = self.send(prep, **send_kwargs)
  File "/usr/local/lib/python3.8/site-packages/requests/sessions.py", line 655, in send
    r = adapter.send(request, **kwargs)
  File "/usr/local/lib/python3.8/site-packages/requests/adapters.py", line 516, in send
    raise ConnectionError(e, request=request)
requests.exceptions.ConnectionError: HTTPConnectionPool(host='host.docker.internal', port=4200): Max retries exceeded with url: / (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f25672ab070>: Failed to establish a new connection: [Errno 111] Connection refused'))

There seem to have been similar or related issues in the past: https://github.com/PrefectHQ/server/issues/25 https://github.com/PrefectHQ/prefect/issues/2324 / https://github.com/PrefectHQ/prefect/pull/2328 https://github.com/PrefectHQ/prefect/pull/4714 https://github.com/PrefectHQ/prefect/pull/4777 https://github.com/PrefectHQ/prefect/pull/4809 However, they seemed to indicate they should be resolved in the version I'm using (details below), and are closed

Expected Behavior

I would expect the docker agent to be able to run the flow and communicate this back to the server

Reproduction

Shell:

# shell 1 (first)
pip install prefect==0.15.5
prefect server start
# http://localhost:8080

# shell 2 (second)
prefect backend server
prefect create project "Test"
prefect agent docker start --label docker --show-flow-logs

Run Python script to register flow (third):

import prefect
from prefect import task, Flow
from prefect.run_configs import DockerRun
from prefect.storage import Docker


@task
def hello_task():
    logger = prefect.context.get("logger")
    logger.info("Hello world!")


with Flow(
        "hello-flow",
        storage=Docker(
            image_name="my_testing_img",
        ),
        run_config=DockerRun(
            labels=["docker"],
        )
) as flow:
    hello = hello_task()


if __name__ == '__main__':
    flow.register(project_name='Test')

Trigger flow (fourth):

# shell 3 
prefect run --project Test --name "hello-flow"

Environment

Ubuntu 20.04

❯ prefect diagnostics
{
  "config_overrides": {},
  "env_vars": [],
  "system_information": {
    "platform": "Linux-5.11.0-34-generic-x86_64-with-glibc2.29",
    "prefect_backend": "server",
    "prefect_version": "0.15.5",
    "python_version": "3.8.12"
  }
}
❯ docker version
Client: Docker Engine - Community
 Version:           20.10.8
 API version:       1.41
 Go version:        go1.16.6
 Git commit:        3967b7d
 Built:             Fri Jul 30 19:54:27 2021
 OS/Arch:           linux/amd64
 Context:           default
 Experimental:      true

Server: Docker Engine - Community
 Engine:
  Version:          20.10.8
  API version:      1.41 (minimum version 1.12)
  Go version:       go1.16.6
  Git commit:       75249d8
  Built:            Fri Jul 30 19:52:33 2021
  OS/Arch:          linux/amd64
  Experimental:     false
 containerd:
  Version:          1.4.9
  GitCommit:        e25210fe30a0a703442421b0f60afac609f950a3
 runc:
  Version:          1.0.1
  GitCommit:        v1.0.1-0-g4144b63
 docker-init:
  Version:          0.19.0
  GitCommit:        de40ad0

Thanks for taking a look, hopefully this is clear and I haven't overlooked something, let me know if you need any more detail?

This is tracking issue for various reports of network failures when self-hosting Prefect Orion.

Notably, these issues seem focused to usage of Prefect 2.6.6.

If adding a report to this issue, please include the following information:

• If using Prefect official Docker images for the client or server, provide the image tags
• On the server, we are interested in the Prefect version, the database, and server library versions

prefect version
pip freeze | grep -E '(uvicorn|starlette)'

• On the client, we are interested in Prefect versions and the client HTTP library versions

prefect version
pip freeze | grep -E '(httpx|httpcore)'

• Please include the full traceback for the error
• Check for any related error logs on the server

Related to:

• https://github.com/PrefectHQ/prefect/issues/7472

Summary

Adds task.pipe, which allows for a pipeline-line method chain, e.g. outer(inner(arg)) can be rewritten as inner(arg).pipe(outer).

Changes

• Adds a single method to the base Task class: .pipe

Importance

Discussion of pipe operators exist in nearly all languages. Bash and other shells have the | pipe operator built-in. The R language has recently implemented a native pipe |>. A proposal for pipes in JavaScript was highly popular. In the Python world, Pandas has a DataFrame.pipe method which has the exact same motivations for chaining function calls when an appropriate DataFrame method doesn't exist. Workflow languages, which belong to the same class of software as Prefect, often have such pipe operators. For example nextflow recently added the pipe operator.

Firstly, a pipe allows for "cleaner" code when large numbers of functions are composed. If for example we wanted to call 5 different tasks in Prefect, we might do task_5(task_4(task_3(task_2(task_1(arg))))). This has two issues: firstly, this needs to be read right-to-left instead of left-to-right as in most code. Secondly, it's very ugly.

We might instead decide to put each task call on each line:

res_1 = task_1(arg)
res_2 = task_2(res_1)
res_3 = task_3(res_2)
res_4 = task_4(res_3)
res_5 = task_5(res_4)

This fixes the right-to-left issue, but forces us to assign intermediate variables to each result. This increases the mental effort involved in writing a flow ("what is the meaning of this result?"), but also pollutes the namespace, and it is very easy to mix up the result from one task with the result from another.

Using pipes solves all of these issues:

task_1(arg).pipe(task_2).pipe(task_3).pipe(task_4).pipe(task_5)

There is perhaps some argument that the .pipe is too verbose, but it helps with clarity. In theory this could be improved by shortening the method name or instead overriding an operator like |.

Checklist

This PR:

• [x] adds new tests (if appropriate)
• [ ] adds a change file in the changes/ directory (if appropriate)
• [x] updates docstrings for any new functions or function arguments, including docs/outline.toml for API reference docs (if appropriate)

$ python --version
Python 3.5.2

(prefect) user@xxxxxx:~/code/prefect$ pipenv install prefect
Installing prefect…
Collecting prefect
  Downloading https://files.pythonhosted.org/packages/c3/86/6599cd54083875df820e3f980a22788a3e23756d8878f3b0e31a61b74dfe/prefect-0.5.0-py3-none-any.whl (208kB)
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Collecting python-dateutil<3.0,>2.7.3 (from prefect)
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Collecting msgpack (from distributed<2.0,>=1.21.8->prefect)
  Downloading https://files.pythonhosted.org/packages/3d/44/4a8be4f56ab3c8fc58800c06b2d681d5622704746d094411f00e25300072/msgpack-0.6.1-cp35-cp35m-manylinux1_x86_64.whl (243kB)
Collecting psutil>=5.0 (from distributed<2.0,>=1.21.8->prefect)
  Downloading https://files.pythonhosted.org/packages/2f/b8/11ec5006d2ec2998cb68349b8d1317c24c284cf918ecd6729739388e4c56/psutil-5.6.1.tar.gz (427kB)
Collecting certifi>=2017.4.17 (from requests<3.0,>=2.20->prefect)
  Downloading https://files.pythonhosted.org/packages/60/75/f692a584e85b7eaba0e03827b3d51f45f571c2e793dd731e598828d380aa/certifi-2019.3.9-py2.py3-none-any.whl (158kB)
Collecting chardet<3.1.0,>=3.0.2 (from requests<3.0,>=2.20->prefect)
  Downloading https://files.pythonhosted.org/packages/bc/a9/01ffebfb562e4274b6487b4bb1ddec7ca55ec7510b22e4c51f14098443b8/chardet-3.0.4-py2.py3-none-any.whl (133kB)
Collecting urllib3<1.25,>=1.21.1 (from requests<3.0,>=2.20->prefect)
  Downloading https://files.pythonhosted.org/packages/62/00/ee1d7de624db8ba7090d1226aebefab96a2c71cd5cfa7629d6ad3f61b79e/urllib3-1.24.1-py2.py3-none-any.whl (118kB)
Collecting docker-pycreds>=0.4.0 (from docker<4.0,>=3.4.1->prefect)
  Downloading https://files.pythonhosted.org/packages/f5/e8/f6bd1eee09314e7e6dee49cbe2c5e22314ccdb38db16c9fc72d2fa80d054/docker_pycreds-0.4.0-py2.py3-none-any.whl
Collecting websocket-client>=0.32.0 (from docker<4.0,>=3.4.1->prefect)
  Downloading https://files.pythonhosted.org/packages/29/19/44753eab1fdb50770ac69605527e8859468f3c0fd7dc5a76dd9c4dbd7906/websocket_client-0.56.0-py2.py3-none-any.whl (200kB)
Collecting cffi!=1.11.3,>=1.8 (from cryptography<3.0,>=2.2.2->prefect)
  Downloading https://files.pythonhosted.org/packages/5b/44/fdae2a8f66af426055f9b6fff0b155217081eddaf08a3df79ca11fe05bda/cffi-1.12.2-cp35-cp35m-manylinux1_x86_64.whl (428kB)
Collecting asn1crypto>=0.21.0 (from cryptography<3.0,>=2.2.2->prefect)
  Downloading https://files.pythonhosted.org/packages/ea/cd/35485615f45f30a510576f1a56d1e0a7ad7bd8ab5ed7cdc600ef7cd06222/asn1crypto-0.24.0-py2.py3-none-any.whl (101kB)
Collecting typed-ast<1.4.0,>=1.3.1 (from mypy<0.700,>=0.600->prefect)
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Collecting heapdict (from zict>=0.1.3->distributed<2.0,>=1.21.8->prefect)
  Downloading https://files.pythonhosted.org/packages/e2/ca/f5feba2f939c97629dbce52a17acc95a0d10256ef620334795379dda8ce6/HeapDict-1.0.0.tar.gz
Collecting pycparser (from cffi!=1.11.3,>=1.8->cryptography<3.0,>=2.2.2->prefect)
  Downloading https://files.pythonhosted.org/packages/68/9e/49196946aee219aead1290e00d1e7fdeab8567783e83e1b9ab5585e6206a/pycparser-2.19.tar.gz (158kB)
Building wheels for collected packages: pyyaml, toolz, tornado, psutil, heapdict, pycparser
  Building wheel for pyyaml (setup.py): started
  Building wheel for pyyaml (setup.py): finished with status 'done'
  Stored in directory: /home/user/.cache/pipenv/wheels/ad/da/0c/74eb680767247273e2cf2723482cb9c924fe70af57c334513f
  Building wheel for toolz (setup.py): started
  Building wheel for toolz (setup.py): finished with status 'done'
  Stored in directory: /home/user/.cache/pipenv/wheels/f4/0c/f6/ce6b2d1aa459ee97cc3c0f82236302bd62d89c86c700219463
  Building wheel for tornado (setup.py): started
  Building wheel for tornado (setup.py): finished with status 'done'
  Stored in directory: /home/user/.cache/pipenv/wheels/61/7e/7a/5e02e60dc329aef32ecf70e0425319ee7e2198c3a7cf98b4a2
  Building wheel for psutil (setup.py): started
  Building wheel for psutil (setup.py): finished with status 'done'
  Stored in directory: /home/user/.cache/pipenv/wheels/86/36/f4/e1fc49f198c623b8dc2156e80011a52f19a959d538f6b1a5db
  Building wheel for heapdict (setup.py): started
  Building wheel for heapdict (setup.py): finished with status 'done'
  Stored in directory: /home/user/.cache/pipenv/wheels/40/b9/42/344857b482c954f48bcff6db72d388e30bf2bee4ed14706faa
  Building wheel for pycparser (setup.py): started
  Building wheel for pycparser (setup.py): finished with status 'done'
  Stored in directory: /home/user/.cache/pipenv/wheels/f2/9a/90/de94f8556265ddc9d9c8b271b0f63e57b26fb1d67a45564511
Successfully built pyyaml toolz tornado psutil heapdict pycparser
Installing collected packages: marshmallow, marshmallow-oneofschema, six, python-dateutil, pytzdata, pendulum, toolz, pyyaml, heapdict, zict, dask, sortedcontainers, click, tornado, tblib, cloudpickle, msgpack, psutil, distributed, idna, certifi, chardet, urllib3, requests, xxhash, toml, docker-pycreds, websocket-client, docker, pycparser, cffi, asn1crypto, cryptography, pytz, mypy-extensions, typed-ast, mypy, croniter, typing, typing-extensions, prefect
Successfully installed asn1crypto-0.24.0 certifi-2019.3.9 cffi-1.12.2 chardet-3.0.4 click-7.0 cloudpickle-0.6.1 croniter-0.3.29 cryptography-2.6.1 dask-1.1.4 distributed-1.26.0 docker-3.7.1 docker-pycreds-0.4.0 heapdict-1.0.0 idna-2.7 marshmallow-3.0.0b19 marshmallow-oneofschema-2.0.0b2 msgpack-0.6.1 mypy-0.670 mypy-extensions-0.4.1 pendulum-2.0.4 prefect-0.5.0 psutil-5.6.1 pycparser-2.19 python-dateutil-2.8.0 pytz-2018.9 pytzdata-2018.9 pyyaml-3.13 requests-2.21.0 six-1.12.0 sortedcontainers-2.1.0 tblib-1.3.2 toml-0.10.0 toolz-0.9.0 tornado-6.0.2 typed-ast-1.3.1 typing-3.6.6 typing-extensions-3.7.2 urllib3-1.24.1 websocket-client-0.56.0 xxhash-1.3.0 zict-0.1.4

Adding prefect to Pipfile's [packages]…
Pipfile.lock not found, creating…
Locking [dev-packages] dependencies…
Locking [packages] dependencies…

Warning: Your dependencies could not be resolved. You likely have a mismatch in your sub-dependencies.
  First try clearing your dependency cache with $ pipenv lock --clear, then try the original command again.
 Alternatively, you can use $ pipenv install --skip-lock to bypass this mechanism, then run $ pipenv graph to inspect the situation.
  Hint: try $ pipenv lock --pre if it is a pre-release dependency.
Could not find a version that matches marshmallow-oneofschema<3.0,>=2.0.0b2
Tried: 1.0, 1.0.1, 1.0.2, 1.0.3, 1.0.3, 1.0.4, 1.0.4, 1.0.5, 1.0.5
Skipped pre-versions: 2.0.0b1, 2.0.0b1, 2.0.0b2, 2.0.0b2
There are incompatible versions in the resolved dependencies.

Opened from the Prefect Public Slack Community

christian.vogel: Hi Prefect Community, I am currently receiving an error when using a local (on my pc) prefect agent which pulls from a work queue in the the prefect cloud. The error only occurs when I try to use the RayTaskRunner:

(begin_task_run pid=141324) ImportError: cannot import name 'SubprocessFlowRunner' from partially initialized module 'prefect.flow_runners' (most likely due to a circular import) (/home/christian/Documents/ray_and_prefect/env/lib/python3.9/site-packages/prefect/flow_runners/__init__.py)

I am using the following dependencies: prefect==2.0b7 prefect-ray==0.1.0 ray==1.13.0 Apparently I am doing something wrong with my dependencies or when I am importing them. Do you have any idea?

christian.vogel: This is my flow and deployment:

from prefect import task, flow
from prefect_ray import RayTaskRunner
from prefect.deployments import DeploymentSpec


@task
def say_hello(name):
    print(f"hello {name}")


@flow(name="temp-flow-example", task_runner=RayTaskRunner(address="auto"))
def greetings():
    say_hello("Ford")


DeploymentSpec(
    name="temp-flow-example",
    flow=greetings
)

christian.vogel: What confuses me a bit, is the fact, that the flow only fails when pulled from the cloud and seems to work when i run it directly locally via python and a main method.

christian.vogel: Could it be related to the fact that I am running my agent in a virtual environment? Probably in the background the following is executed:

from prefect.flow_runners import SubprocessFlowRunner

which them leads to some import issues because of the already imported:

from prefect_ray import RayTaskRunner

Is that possible?

anna: do you run your agent in the same virtual environment as you run your local process? perhaps you can explicitly define your flow runner with the virtual environment you use for your agent?

flow_runner=SubprocessFlowRunner(condaenv="yourcondavenv"),

anna: I was trying to replicate and sth also didn't work for me, even though I got a different error message using the same versions as you did

anna: my error was:

Failed to read dashboard log: [Errno 2] No such file or directory: '/tmp/ray/session_2022-07-07_14-08-35_008202_6668/logs/dashboard.log'

anna: wow it took me forever to set this up but this helped https://docs.ray.io/en/master/ray-overview/installation.html#m1-mac-apple-silicon-support

looks like you need to be super careful about your environment with Ray and grpcio package - do you use Conda? on which machine do you run it?

christian.vogel: Tried specifying the SubprocessFlowRunner with the virtual env path in my case. but did not help

christian.vogel: I am running a venv on a linux ubuntu machine

anna: yup you're right, I was able to reproduce your error, thanks for reporting that

<@ULVA73B9P> open "Flow run with Ray and agent throws: ImportError: cannot import name 'SubprocessFlowRunner' from partially initialized module 'prefect.flow_runners'"

Original thread can be found here.

Summary

PR to add the ability to use capacity providers in ECS Agent and ECSRun when set in run_task_kwargs

Changes

• Updates the way ECSAgent set's the launchType and default network configuration when a capacity provider is passed in via run-task-kwargs.

• Deletes launchType in ECSAgent run_config (opts) in merge_run_task_kwargs if capacityProvider is found in ECSRun's run_config (opts2) and vice versa

Importance

Being able to use capacity providers in ECS enables the use of Fargate Spot and ASG's.

Found in Issues: #4356 and #5210

Checklist

This PR:

• [x] adds new tests (if appropriate)
• [x] adds a change file in the changes/ directory (if appropriate)
• [x] updates docstrings for any new functions or function arguments, including docs/outline.toml for API reference docs (if appropriate)

First check

• [X] I added a descriptive title to this issue.
• [X] I used the GitHub search to find a similar issue and didn't find it.
• [X] I searched the Prefect documentation for this issue.
• [X] I checked that this issue is related to Prefect and not one of its dependencies.

Bug summary

1. Having a main flow which uses sequential task runner, calling a subflow which just calls the .map function on the task trying to create parallel task runs.
2. few of those tasks crash , giving AssertionError

Reproduction

from prefect import task, flow
from prefect import get_run_logger
import time
from prefect.task_runners import SequentialTaskRunner


@task(name='run_scheduler')
def run_scheduler(event):
    scheduler_output = [i for i in range(1, 300)]
    time.sleep(150)  # Adding sleep time to make task bit long running
    return scheduler_output


@task(name='run_executor', tags=['spends_executor'])
def run_executor(scheduler_output):
    time.sleep(150)  # Adding sleep time to make task bit long running
    executor_output = f"printing just the executor input {scheduler_output}"
    return executor_output


@flow(task_runner=SequentialTaskRunner())
def spends_flow(event):
    logger = get_run_logger()
    logger.info(event)

    # Calling Scheduler task
    scheduler_output = run_scheduler(event)

    # if the output is empty array just log it else calling subflow which creates parallel task executions

    if len(scheduler_output) < 1:
        logger.info("no elements in array")
    else:
        spends_executor(scheduler_output)
    logger.info('flow completed')


@flow
def spends_executor(scheduler_output):
    run_executor.map(scheduler_output)


if __name__ == "__main__":
    event = "test"
    spends_flow(event)

Error

Encountered exception during execution:
Traceback (most recent call last):
  File "/usr/local/lib/python3.9/site-packages/prefect/engine.py", line 1247, in orchestrate_task_run
    result = await run_sync(task.fn, *args, **kwargs)
  File "/usr/local/lib/python3.9/site-packages/prefect/utilities/asyncutils.py", line 68, in run_sync_in_worker_thread
    return await anyio.to_thread.run_sync(call, cancellable=True)
  File "/usr/local/lib/python3.9/site-packages/anyio/to_thread.py", line 31, in run_sync
    return await get_asynclib().run_sync_in_worker_thread(
  File "/usr/local/lib/python3.9/site-packages/anyio/_backends/_asyncio.py", line 937, in run_sync_in_worker_thread
    return await future
  File "/usr/local/lib/python3.9/site-packages/anyio/_backends/_asyncio.py", line 867, in run
    result = context.run(func, *args)
  File "flows/test_calculate_spends_flows/test_spends_flow.py", line 16, in run_executor
    output = run_deployment(
  File "/usr/local/lib/python3.9/site-packages/prefect/utilities/asyncutils.py", line 197, in coroutine_wrapper
    return run_async_from_worker_thread(async_fn, *args, **kwargs)
  File "/usr/local/lib/python3.9/site-packages/prefect/utilities/asyncutils.py", line 148, in run_async_from_worker_thread
    return anyio.from_thread.run(call)
  File "/usr/local/lib/python3.9/site-packages/anyio/from_thread.py", line 49, in run
    return asynclib.run_async_from_thread(func, *args)
  File "/usr/local/lib/python3.9/site-packages/anyio/_backends/_asyncio.py", line 970, in run_async_from_thread
    return f.result()
  File "/usr/local/lib/python3.9/concurrent/futures/_base.py", line 446, in result
    return self.__get_result()
  File "/usr/local/lib/python3.9/concurrent/futures/_base.py", line 391, in __get_result
    raise self._exception
  File "/usr/local/lib/python3.9/site-packages/prefect/client/utilities.py", line 47, in with_injected_client
    return await fn(*args, **kwargs)
  File "/usr/local/lib/python3.9/site-packages/prefect/deployments.py", line 131, in run_deployment
    flow_run = await client.read_flow_run(flow_run_id)
  File "/usr/local/lib/python3.9/site-packages/prefect/client/orion.py", line 1443, in read_flow_run
    response = await self._client.get(f"/flow_runs/{flow_run_id}")
  File "/usr/local/lib/python3.9/site-packages/httpx/_client.py", line 1757, in get
    return await self.request(
  File "/usr/local/lib/python3.9/site-packages/httpx/_client.py", line 1533, in request
    return await self.send(request, auth=auth, follow_redirects=follow_redirects)
  File "/usr/local/lib/python3.9/site-packages/prefect/client/base.py", line 160, in send
    await super().send(*args, **kwargs)
  File "/usr/local/lib/python3.9/site-packages/httpx/_client.py", line 1620, in send
    response = await self._send_handling_auth(
  File "/usr/local/lib/python3.9/site-packages/httpx/_client.py", line 1648, in _send_handling_auth
    response = await self._send_handling_redirects(
  File "/usr/local/lib/python3.9/site-packages/httpx/_client.py", line 1685, in _send_handling_redirects
    response = await self._send_single_request(request)
  File "/usr/local/lib/python3.9/site-packages/httpx/_client.py", line 1722, in _send_single_request
    response = await transport.handle_async_request(request)
  File "/usr/local/lib/python3.9/site-packages/httpx/_transports/default.py", line 353, in handle_async_request
    resp = await self._pool.handle_async_request(req)
  File "/usr/local/lib/python3.9/site-packages/httpcore/_async/connection_pool.py", line 221, in handle_async_request
    await self._attempt_to_acquire_connection(status)
  File "/usr/local/lib/python3.9/site-packages/httpcore/_async/connection_pool.py", line 160, in _attempt_to_acquire_connection
    status.set_connection(connection)
  File "/usr/local/lib/python3.9/site-packages/httpcore/_async/connection_pool.py", line 22, in set_connection
    assert self.connection is None
AssertionError

Versions

agent
Version:             2.6.6
API version:         0.8.3
Python version:      3.9.15
Git commit:          87767cda
Built:               Thu, Nov 3, 2022 1:15 PM
OS/Arch:             linux/x86_64
Profile:             default
Server type:         hosted

self hosted orion server
Version:             2.6.0
API version:         0.8.2
Python version:      3.9.14
Git commit:          96f09a51
Built:               Thu, Oct 13, 2022 3:21 PM
OS/Arch:             linux/x86_64
Profile:             default
Server type:         hosted

Additional context

No response

Description

A dealbreaker that deterred me from using v2.0 (since it has async support) is not having bulk selection of flows to delete them. It's cumbersome to delete one by one, especially if you have a lot of flow runs. Having this feature would be great to enhance the UX.

Opened from the Prefect Public Slack Community

dkmarsh: Hi Everyone, I'm having an issue with registering flows. Whenever I register the same flow, it bumps the version, even if the metadata is unchanged. I've tried using the CLI as well as flow.register(). I've also tried using flow.register('project_1', idempotency_key=flow.serialized_hash()) and it still bumps the version. I am using a local agent, local storage and the cloud backend. Is there another configuration that needs to be set so this doesn't happen? Or should this all be done in docker?

kevin701: Hey <@U022J2DB0UR>, I don’t think moving to Docker will do this. Will ask the team to be sure but what is your use case that you need the version pinned? We might be able to solve this some other way.

ranugoldan: I once tried with cli command prefect register flow it doesn't bump version, but with prefect register it does

kevin701: Actually that’s right <@ULCV623AT>! I know some people on the other side have been asking why their flow is not bumping version :sweat_smile:

amanda.wee: <@U01QEJ9PP53> when should the flow version be bumped? In my ECS-based setup with a bunch of flows packaged together with a local agent, I build the Docker image each time we make a change, even if it is only to tweak a single task. When the Docker container starts up, it runs a shell script that runs the Python scripts that define and register the flows (i.e., not using the CLI). Like what <@ULCV623AT> observed, with serialized_hash() the flow versions kept increasing even if it was just because the ECS task was restarted, thereby starting up the Docker container again.

My suspicion was that some Docker container metadata was changing each time, e.g., something host-related, so the serialized hash computation changed. My solution was to write my own hash function that took into account the dependencies (including Prefect version) and the code content, but I wonder if that is overkill.

kevin701: Hey <@U01DJDK6AQ7>, correct me if I’m wrong but I think what you’re referring to is that DockerStorage was not respecting the cache and rebuilding everything. Have you seen this <https://github.com/PrefectHQ/prefect/pull/4584|recent PR> that fixed it?.

amanda.wee: No, I'm using S3 storage. The Docker image is for ECS, not for Prefect.

kevin701: Oh I see what you mean. Ok I’ll ask the team and get back to you

dkmarsh: <@U01QEJ9PP53> It was my understanding that the version should only be bumped when the metadata changes. My use case is to automate the registering of flows once they are added or changed by a developer. I wrote a function that looks in a directory and collects all flows and registers them. I would like to not have the versions bumped on flows that have already been registered and have had no changes.

Interestingly enough, I tried testing again this morning and discovered that in using the CLI or python api to register, the version will get bumped every other time. For example, if I run prefect register --project Project1 -p src/register.py -n Flow1 it will register the flow, then if I run the same command a few seconds later, it will skip with the message: "Skipped (metadata unchanged)". However, running it a third time, it will register the flow as version 2. So it seems to be skipping the registration as desired every other time.

znicholasbrown: Hi <@U022J2DB0UR> - this sounds like an issue with CLI registration; I'm going to open an issue from this thread for the Core team to look into.

znicholasbrown: <@ULVA73B9P> open "CLI registration inconsistently bumps flow version even when metadata hasn't changed"

Original thread can be found here.

First check

• [X] I added a descriptive title to this issue.
• [X] I used the GitHub search to find a similar issue and didn't find it.
• [X] I searched the Prefect documentation for this issue.
• [X] I checked that this issue is related to Prefect and not one of its dependencies.

Bug summary

The state pill in each FlowRunList item on the Flow Runs page is Unknown, without state color. However, the scatterplot shows the color for the state of each flow run.

Reproduction

N/A

Error

No response

Versions

The user is using Prefect 2.75

Additional context

Community slack thread

Moves SQLALCHEMY_SILENCE_UBER_WARNING to setup.cfg so that it disables warnings on local test runs as well as in CI.

Checklist

• [ ] This pull request references any related issue by including "closes <link to issue>"
  • If no issue exists and your change is not a small fix, please create an issue first.
• [x] This pull request includes tests or only affects documentation.
• [x] This pull request includes a label categorizing the change e.g. fix, feature, enhancement

First check

• [X] I am a contributor to the Prefect codebase

Description

Tracking issue for migrating to SQLAlchemy 2.0 using the migration guide. When migrating, the changes in #8042 can be removed.

Impact

No response

Additional context

No response

To merge this PR changes from orion-design should be released and merged first

Example

Checklist

• [ ] This pull request references any related issue by including "closes <link to issue>"
  • If no issue exists and your change is not a small fix, please create an issue first.
• [ ] This pull request includes tests or only affects documentation.
• [ ] This pull request includes a label categorizing the change e.g. fix, feature, enhancement

First check

• [X] I added a descriptive title to this issue.
• [X] I used the GitHub search to find a similar issue and didn't find it.
• [X] I searched the Prefect documentation for this issue.
• [X] I checked that this issue is related to Prefect and not one of its dependencies.

Bug summary

I have a flow that runs spark job using prefect-databricks connector. If the job is running for more than 4hrs, flow in prefect is marked as crashed after 4hrs + 1-4 minutes

Reproduction

# Kubernetes job infra defined as

k8s_job = KubernetesJob(
        namespace=namespace,
        image=image_name,
        image_pull_policy=KubernetesImagePullPolicy.ALWAYS,
        finished_job_ttl=300,
        service_account_name="prefect-server",
        job_watch_timeout_seconds=180,
        customizations={ .. volumes & secrets here },
        env={
            .. bunch of envs here.. 
        }
    )

# images is custom built on top of the 2.7.4 prefect:

ARG PREFECT_VERSION=2.7.4
ARG PYTHON_VERSION=python3.10
FROM prefecthq/prefect:${PREFECT_VERSION}-${PYTHON_VERSION}


# databricks job is submitted like this:

@flow
def databricks_run_reload(notebook_path, params):

    # compile job task settings
    job_task_settings = JobTaskSettings(
        new_cluster=new_cluster,
        notebook_task=spark_python_notebook_task,
        task_key=task_key,
        timeout_seconds=86400,
        libraries=[]
    )

    idempotency_key = str(uuid.uuid4())
    multi_task_runs = jobs_runs_submit_and_wait_for_completion(
        databricks_credentials=databricks_credentials,
        run_name=run_name,
        git_source=git,
        tasks=[job_task_settings],
        max_wait_seconds=86400,
        idempotency_token=idempotency_key
    )
    return multi_task_runs

# and used in other flow:

@flow
# @flow(persist_result=True, result_storage=S3.load(config.DEFAULT_S3_BLOCK_NAME)) ## tried this as well, but no difference
def do_reload():
    spark = databricks_run_reload(notebook_path="some_notebook", some_params)
    updated = execute_dml(merge_query, params=query_params, wait_for=[spark])

Error

Traceback (most recent call last):
  File "/usr/local/lib/python3.10/site-packages/prefect/engine.py", line 637, in orchestrate_flow_run
    result = await run_sync(flow_call)
  File "/usr/local/lib/python3.10/site-packages/prefect/utilities/asyncutils.py", line 91, in run_sync_in_worker_thread
    return await anyio.to_thread.run_sync(
  File "/usr/local/lib/python3.10/site-packages/anyio/to_thread.py", line 31, in run_sync
    return await get_asynclib().run_sync_in_worker_thread(
  File "/usr/local/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 937, in run_sync_in_worker_thread
    return await future
  File "/usr/local/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 867, in run
    result = context.run(func, *args)
  File "/opt/prefect/flows/spark.py", line 45, in do_reload
    updated = execute_dml(query, params=query_params, wait_for=[spark])
  File "/usr/local/lib/python3.10/site-packages/prefect/tasks.py", line 436, in __call__
    return enter_task_run_engine(
  File "/usr/local/lib/python3.10/site-packages/prefect/engine.py", line 927, in enter_task_run_engine
    return run_async_from_worker_thread(begin_run)
  File "/usr/local/lib/python3.10/site-packages/prefect/utilities/asyncutils.py", line 177, in run_async_from_worker_thread
    return anyio.from_thread.run(call)
  File "/usr/local/lib/python3.10/site-packages/anyio/from_thread.py", line 49, in run
    return asynclib.run_async_from_thread(func, *args)
  File "/usr/local/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 970, in run_async_from_thread
    return f.result()
  File "/usr/local/lib/python3.10/concurrent/futures/_base.py", line 458, in result
    return self.__get_result()
  File "/usr/local/lib/python3.10/concurrent/futures/_base.py", line 403, in __get_result
    raise self._exception
  File "/usr/local/lib/python3.10/site-packages/prefect/engine.py", line 1068, in get_task_call_return_value
    return await future._result()
  File "/usr/local/lib/python3.10/site-packages/prefect/futures.py", line 237, in _result
    return await final_state.result(raise_on_failure=raise_on_failure, fetch=True)
  File "/usr/local/lib/python3.10/site-packages/prefect/states.py", line 100, in _get_state_result
    raise MissingResult(
prefect.exceptions.MissingResult: State data is missing. Typically, this occurs when result persistence is disabled and the state has been retrieved from the API.

Versions

Version:             2.7.4
API version:         0.8.4
Python version:      3.10.8
Git commit:          30db76e7
Built:               Thu, Dec 22, 2022 2:55 PM
OS/Arch:             linux/x86_64
Profile:             dev
Server type:         hosted

Additional context

No response

with the recent PR that adds feature flags to orion-design, nebula and orion-ui will both need to update it's Permissions type to include the possibility of WorkspaceFeatureFlag