< Marvin> I m running Prefect self hosted using Docker and I Prefect Community #ask-marvin

<@ULVA73B9P> I'm running Prefect self-hosted using...

Caio Henrique

07/21/2025, 1:19 AM

@Marvin I'm running Prefect self-hosted using Docker and I'm trying to set up my deployments to pull the flow code from a public GitHub repository using the recommended git_clone pull step in my prefect.yaml. However, every time a flow run starts, I get the following error inside the execution container: Apply to prefect.yaml fatal: not a git repository (or any of the parent directories): .git I've confirmed that: • The worker container has internet access and can reach GitHub. • The repository is public and accessible. • My prefect.yaml includes the git_clone step, and I also tried adding set_working_directory as suggested in the docs. • The entrypoint is correct and relative to the repo root. Despite this, the flow run always fails with the git error above, as if the code is not being cloned or the entrypoint is not being executed in the right directory. How can I ensure that the flow code is properly cloned and the entrypoint is executed in the correct directory inside the Docker execution container? Is there any known issue or extra configuration needed for this to work with Docker work pools? Thanks for your help!

Marvin

07/21/2025, 1:19 AM

✅ thought for 64.7 seconds

Marvin

07/21/2025, 1:20 AM

Based on the research and the GitHub issues, I can help diagnose and fix your issue. The problem you're experiencing is related to how the git clone operation is being handled in the Docker container environment. Here's how to resolve it: 1. Add a cleanup step The most important fix is to ensure the target directory is clean before cloning. You can do this by adding a

shell_command

step before the

git_clone

step in your

prefect.yaml

. Here's how your pull steps should look:

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yaml
pull:
  - prefect.deployments.steps.set_working_directory:
      directory: "/opt/prefect/flows"  # or your preferred directory
  - prefect.deployments.steps.shell_command:
      command: "rm -rf repo"  # replace 'repo' with your target directory name
  - prefect.deployments.steps.git_clone:
      repository: "<https://github.com/your/repository>"
      branch: "main"  # specify your branch
  - prefect.deployments.steps.set_working_directory:
      directory: "/opt/prefect/flows/repo"  # adjust path to match your setup

2. Ensure proper directory structure Make sure your directory paths are consistent throughout the configuration. The error suggests that the working directory might not be properly set or maintained between runs. 3. Verify Docker container permissions Ensure that the user running the Prefect worker in the Docker container has write permissions to the directory where you're trying to clone the repository. 4. Check your prefect.yaml entrypoint Make sure your entrypoint is correctly specified relative to where the code is being cloned. For example:

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yaml
deployments:
  - name: your-deployment
    entrypoint: "flow.py:your_flow"  # relative to the repo root
    work_pool:
      name: your-docker-pool

5. Docker work pool configuration Verify that your Docker work pool configuration includes: - Proper working directory configuration - Appropriate volume mounts if needed - Correct base image with git installed To verify your setup works, you can: 1. First check if git is available in your container:

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bash
docker exec your-container-name git --version

2. Try manually cloning the repository in the container:

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bash
docker exec your-container-name git clone your-repository-url

If you're still having issues, could you please share: 1. The complete content of your

prefect.yaml

file (with sensitive information redacted)? 2. The Docker work pool configuration you're using? 3. The base Docker image you're using for your worker? This will help me provide more specific guidance for your setup. Also, as a best practice for Docker-based deployments in Prefect 3.x, consider using the

from_source()

method when creating deployments programmatically, as it provides a more streamlined way to handle Git-based deployments:

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python
from prefect import flow
from prefect.deployments import Deployment

@flow
def my_flow():
    pass

deployment = flow.from_source(
    source="<https://github.com/your/repository.git>",
    entrypoint="flow.py:my_flow"
).deploy(
    name="my-deployment",
    work_pool_name="your-docker-pool"
)

This approach can sometimes be more reliable than managing the git clone steps manually in the

prefect.yaml

file.

Caio Henrique

07/21/2025, 1:36 AM

name: mds-flows pull: - prefect.deployments.steps.git_clone: repository: https://github.com/caiohmb/mdsstack.git branch: "main" - prefect.deployments.steps.set_working_directory: directory: "/opt/prefect/mdsstack" # adjust path to match your setup deployments: - name: ingestao-dlt-clima entrypoint: flows/flow.py:run_dlt_ingestion work_pool: name: "local-pool" schedule: cron: "0 6 * * *" timezone: "America/Sao_Paulo"

Caio Henrique

07/21/2025, 1:36 AM

@Marvin name: mds-flows pull: - prefect.deployments.steps.git_clone: repository: https://github.com/caiohmb/mdsstack.git branch: "main" - prefect.deployments.steps.set_working_directory: directory: "/opt/prefect/mdsstack" # adjust path to match your setup deployments: - name: ingestao-dlt-clima entrypoint: flows/flow.py:run_dlt_ingestion work_pool: name: "local-pool" schedule: cron: "0 6 * * *" timezone: "America/Sao_Paulo" this is my prefect.yml

Marvin

07/21/2025, 1:37 AM

✅ thought for 42.5 seconds

Marvin

07/21/2025, 1:37 AM

Here are the steps to fix your setup: 1. Create a proper Docker work pool:

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bash
prefect work-pool create "docker-pool" --type docker

2. Update your prefect.yaml to use the Docker work pool:

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yaml
deployments:
  - name: ingestao-dlt-clima
    entrypoint: flows/flow.py:run_dlt_ingestion
    work_pool:
      name: "docker-pool"  # Changed from local-pool to docker-pool
    schedule:
      cron: "0 6 * * *"
      timezone: "America/Sao_Paulo"

3. Ensure your Docker container has the necessary setup: - Git should be installed - The

/opt/prefect/flows

directory should exist and be writable - The container should have internet access to reach GitHub 4. Start a worker for your Docker work pool:

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bash
prefect worker start -p docker-pool

To verify everything is set up correctly, try these steps: 1. First, deploy your flow:

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bash
prefect deploy

2. Then run your deployment once manually to test:

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bash
prefect deployment run ingestao-dlt-clima/run_dlt_ingestion

If you're still seeing the git error, could you please: 1. Confirm if you're using the default Docker image or a custom one? 2. Share any error messages you see when running the deployment? 3. Let me know if you have any custom Docker configurations in your work pool settings? This will help me provide more specific guidance for your setup. Also, since you're using a public GitHub repository, you might want to consider using the more modern

from_source()

approach in a Python deployment script:

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python
from prefect import flow
from prefect.deployments import Deployment

@flow
def run_dlt_ingestion():
    # your flow code here
    pass

deployment = flow.from_source(
    source="<https://github.com/caiohmb/mdsstack.git>",
    entrypoint="flows/flow.py:run_dlt_ingestion"
).deploy(
    name="ingestao-dlt-clima",
    work_pool_name="docker-pool",
    schedule={"cron": "0 6 * * *", "timezone": "America/Sao_Paulo"}
)

This approach can be more reliable as it handles the git clone operation more gracefully within the Prefect infrastructure.

Caio Henrique

07/21/2025, 1:39 AM

@Marvin whats name of my file for the deployment?

Marvin

07/21/2025, 1:39 AM

✅ thought for 7.8 seconds

Marvin

07/21/2025, 1:39 AM

For the Python deployment script I suggested, you can name it anything you like, but common conventions are: 1.

deployment.py

create_deployment.py

deploy.py

Here's the complete content for your

deployment.py

file:

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python
from prefect import flow
from prefect.deployments import Deployment

@flow
def run_dlt_ingestion():
    # your flow code here
    pass

if __name__ == "__main__":
    deployment = flow.from_source(
        source="<https://github.com/caiohmb/mdsstack.git>",
        entrypoint="flows/flow.py:run_dlt_ingestion"
    ).deploy(
        name="ingestao-dlt-clima",
        work_pool_name="docker-pool",
        schedule={"cron": "0 6 * * *", "timezone": "America/Sao_Paulo"}
    )

To create the deployment, you would then run:

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bash
python deployment.py

Note that this script references your actual flow code which is in

flows/flow.py

. The

entrypoint

parameter points to this location within your GitHub repository. A few important points: 1. The

@flow

decorator in the deployment script is just a placeholder - your actual flow code remains in

flows/flow.py

2. Make sure the

entrypoint

path matches exactly where your flow function is defined in your repository 3. You can remove your existing

prefect.yaml

if you switch to this deployment method, as all the configuration is now handled in the Python code Would you like me to explain any part of this in more detail?

Caio Henrique

07/21/2025, 1:40 AM

@Marvin how aplly this deployment?

Marvin

07/21/2025, 1:40 AM

✅ thought for 21.9 seconds

Marvin

07/21/2025, 1:40 AM

Here's the complete step-by-step process to apply your deployment: 1. First, create the Docker work pool (if you haven't already):

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bash
prefect work-pool create docker-pool --type docker

2. Create your deployment file Create a new file called

deployment.py

with this content:

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python
from prefect import flow
from prefect.deployments import Deployment

# This is just a placeholder - your actual flow is in your GitHub repo
@flow
def run_dlt_ingestion():
    pass

if __name__ == "__main__":
    deployment = flow.from_source(
        source="<https://github.com/caiohmb/mdsstack.git>",
        entrypoint="flows/flow.py:run_dlt_ingestion"
    ).deploy(
        name="ingestao-dlt-clima",
        work_pool_name="docker-pool",
        schedule={"cron": "0 6 * * *", "timezone": "America/Sao_Paulo"}
    )

3. Apply the deployment

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bash
python deployment.py

4. Start a worker to run your flows:

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bash
prefect worker start -p docker-pool

5. Verify your deployment was created:

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prefect deployment ls

6. Test your deployment by running it once:

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prefect deployment run ingestao-dlt-clima/run_dlt_ingestion

Important Notes: - Make sure you're in the correct directory when running these commands - The worker needs to be running for your flows to execute - Your actual flow code should be in

flows/flow.py

in your GitHub repository - The Docker worker will automatically pull your code from GitHub when running the flow Common Issues to Watch For: 1. If you get a "work pool not found" error, make sure you created the work pool first 2. If the flow doesn't start, make sure you have a worker running 3. If you get git errors, make sure your GitHub repository URL is correct Would you like me to explain any of these steps in more detail? Or would you like to see how to check the status of your deployment after creating it?

Caio Henrique

07/21/2025, 1:42 AM

(venv) PS C:\opt\mds-test\mdsstack> py deployment.py Traceback (most recent call last): File "C:\opt\mds-test\mdsstack\deployment.py", line 2, in <module> from prefect.deployments import Deployment File "C:\opt\mds-test\mdsstack\venv\Lib\site-packages\prefect\deployments\__init__.py", line 23, in getattr return getattr_migration(name)(attr_name) ~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^ File "C:\opt\mds-test\mdsstack\venv\Lib\site-packages\prefect\_internal\compatibility\migration.py", line 156, in wrapper raise PrefectImportError( f"`{import_path}` has been removed. {error_message}" ) prefect.exceptions.PrefectImportError:

prefect.deployments:Deployment

has been removed. Use

flow.serve()

flow.deploy()

, or

prefect deploy

instead. (venv) PS C:\opt\mds-test\mdsstack>

Caio Henrique

07/21/2025, 1:43 AM

@Marvin (venv) PS C:\opt\mds-test\mdsstack> py deployment.py Traceback (most recent call last): File "C:\opt\mds-test\mdsstack\deployment.py", line 2, in <module> from prefect.deployments import Deployment File "C:\opt\mds-test\mdsstack\venv\Lib\site-packages\prefect\deployments\__init__.py", line 23, in getattr return getattr_migration(name)(attr_name) ~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^ File "C:\opt\mds-test\mdsstack\venv\Lib\site-packages\prefect\_internal\compatibility\migration.py", line 156, in wrapper raise PrefectImportError( f"`{import_path}` has been removed. {error_message}" ) prefect.exceptions.PrefectImportError:

prefect.deployments:Deployment

has been removed. Use

flow.serve()

flow.deploy()

, or

prefect deploy

instead. (venv) PS C:\opt\mds-test\mdsstack>

Marvin

07/21/2025, 1:43 AM

✅ thought for 10.1 seconds

Marvin

07/21/2025, 1:43 AM

Ah, I see the issue. You're using Prefect 3.x where the deployment syntax has changed. Let me provide you with the correct, updated code for Prefect 3.x:

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python
from prefect import flow

# This is just a placeholder - your actual flow is in your GitHub repo
@flow
def run_dlt_ingestion():
    pass

if __name__ == "__main__":
    run_dlt_ingestion.from_source(
        source="<https://github.com/caiohmb/mdsstack.git>",
        entrypoint="flows/flow.py:run_dlt_ingestion"
    ).deploy(
        name="ingestao-dlt-clima",
        work_pool_name="docker-pool",
        schedule={"cron": "0 6 * * *", "timezone": "America/Sao_Paulo"}
    )

The key differences in Prefect 3.x are: 1. We don't import

Deployment

anymore 2. We use the flow's

from_source()

method directly 3. We chain it with

.deploy()

to create the deployment Save this as

deployment.py

and then run:

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bash
python deployment.py

If you want to verify the deployment was created successfully, you can run:

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bash
prefect deployment ls

And to start a worker that will run your flows:

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bash
prefect worker start -p docker-pool

To test your deployment immediately:

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bash
prefect deployment run ingestao-dlt-clima/run_dlt_ingestion

Let me know if you get any other errors, and I'll help you resolve them!

Caio Henrique

07/21/2025, 1:50 AM

@Marvin container worker log 014517.067 | INFO | prefect.flow_runs.worker - Worker 'DockerWorker 76a741da-c9b9-4ca6-95b3-fbe658a891c7' submitting flow run 'e1807491-00cf-462d-a08c-69926b35179c' fatal: not a git repository (or any of the parent directories): .git 014517.202 | INFO | prefect.workers.docker.dockerworker 76a741da-c9b9-4ca6-95b3-fbe658a891c7 - Creating Docker container 'vermilion-narwhal'... 014517.203 | INFO | prefect.workers.docker.dockerworker 76a741da-c9b9-4ca6-95b3-fbe658a891c7 - Creating Docker container 'vermilion-narwhal'... 014517.270 | INFO | prefect.workers.docker.dockerworker 76a741da-c9b9-4ca6-95b3-fbe658a891c7 - Docker container 'vermilion-narwhal' has status 'created' 014517.271 | INFO | prefect.workers.docker.dockerworker 76a741da-c9b9-4ca6-95b3-fbe658a891c7 - Docker container 'vermilion-narwhal' created successfully. 014517.572 | INFO | prefect.flow_runs.worker - Completed submission of flow run 'e1807491-00cf-462d-a08c-69926b35179c' 014517.592 | INFO | prefect.workers.docker.dockerworker 76a741da-c9b9-4ca6-95b3-fbe658a891c7 - Docker container 'vermilion-narwhal' has status 'running' File "/usr/local/lib/python3.12/site-packages/prefect/events/clients.py", line 566, in _reconnect self._websocket = await self._connect.__aenter__() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/websockets/asyncio/client.py", line 587, in aenter return await self ^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/prefect/_internal/websockets.py", line 135, in _proxy_connect proto = await self.__await_impl__() ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/websockets/asyncio/client.py", line 541, in __await_impl__ self.connection = await self.create_connection() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/websockets/asyncio/client.py", line 467, in create_connection _, connection = await loop.create_connection(factory, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/asyncio/base_events.py", line 1083, in create_connection infos = await self._ensure_resolved( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/asyncio/base_events.py", line 1466, in _ensure_resolved return await loop.getaddrinfo(host, port, family=family, type=type, ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/asyncio/base_events.py", line 905, in getaddrinfo return await self.run_in_executor( container vermillion-narwhal log raceback (most recent call last): File "/usr/local/lib/python3.12/site-packages/prefect/cli/_utilities.py", line 44, in wrapper An exception occurred. return fn(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/prefect/cli/_types.py", line 156, in sync_fn return asyncio.run(async_fn(*args, **kwargs)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/asyncio/runners.py", line 195, in run return runner.run(main) ^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/asyncio/runners.py", line 118, in run return self._loop.run_until_complete(task) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/asyncio/base_events.py", line 691, in run_until_complete return future.result() ^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/prefect/cli/flow_run.py", line 412, in execute await runner.execute_flow_run(id) File "/usr/local/lib/python3.12/site-packages/prefect/runner/runner.py", line 571, in execute_flow_run async with context: ^^^^^^^ File "/usr/local/lib/python3.12/site-packages/prefect/runner/runner.py", line 1498, in aenter await self._exit_stack.enter_async_context( File "/usr/local/lib/python3.12/contextlib.py", line 659, in enter_async_context result = await _enter(cm) ^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/prefect/runner/_observers.py", line 42, in aenter self._events_subscriber = await self._exit_stack.enter_async_context( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/contextlib.py", line 659, in enter_async_context result = await _enter(cm) ^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.12/site-packages/prefect/events/clients.py", line 555, in aenter await self._reconnect() File "/usr/local/lib/python3.12/site-packages/prefect/events/clients.py", line 566, in _reconnect self._websocket = await self._connect.__aenter__() the deployment from prefect import flow @flow def run_dlt_ingestion(): pass if name == "__main__": run_dlt_ingestion.from_source( source="https://github.com/caiohmb/mdsstack.git", entrypoint="flows/flow.py:run_dlt_ingestion" ).deploy( name="ingestao-dlt-clima", _work_pool_name_="local-pool", schedule={"cron": "0 6 * * *", "timezone": "America/Sao_Paulo"} )

Marvin

07/21/2025, 1:50 AM

✅ thought for 19.6 seconds

Marvin

07/21/2025, 1:50 AM

I notice a few issues in your setup. Let's fix them: 1. First, you're using "local-pool" in your deployment but running a Docker worker. Let's make sure we're consistent with the work pool setup. 2. The git error suggests there might be an issue with how the repository is being cloned in the Docker container. Here's the corrected deployment script (

deployment.py

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python
from prefect import flow

@flow
def run_dlt_ingestion():
    pass

if __name__ == "__main__":
    run_dlt_ingestion.from_source(
        source="<https://github.com/caiohmb/mdsstack.git>",
        entrypoint="flows/flow.py:run_dlt_ingestion"
    ).deploy(
        name="ingestao-dlt-clima",
        work_pool_name="docker-pool",  # Changed from local-pool to docker-pool
        job_variables={
            "image": "prefecthq/prefect:2-python3.12",  # Specify the Docker image
            "volumes": ["/opt/prefect/flows:/opt/prefect/flows"]  # Mount volume for persistence
        }
    )

Now, let's set up everything step by step: 1. First, create the Docker work pool:

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bash
prefect work-pool create docker-pool --type docker

2. Apply the deployment:

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bash
python deployment.py

3. Start the Docker worker (make sure Docker is running on your machine):

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bash
prefect worker start -p docker-pool

4. Check your project structure Your repository structure should look like this:

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mdsstack/
├── flows/
│   └── flow.py  # Contains your actual flow code
└── deployment.py

5. Verify the content of your
flows/flow.py
Make sure your actual flow code in the GitHub repository matches this structure:

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python
from prefect import flow

@flow
def run_dlt_ingestion():
    # Your actual flow code here
    pass

if __name__ == "__main__":
    run_dlt_ingestion()

To test the deployment: 1. First, delete the existing deployment:

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bash
prefect deployment delete ingestao-dlt-clima/run_dlt_ingestion

2. Apply the new deployment:

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bash
python deployment.py

3. Test the deployment:

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bash
prefect deployment run ingestao-dlt-clima/run_dlt_ingestion

If you're still seeing issues, could you please: 1. Confirm the exact path to your flow code in your GitHub repository? 2. Share the content of your actual flow code from

flows/flow.py

? 3. Run this command and share the output:

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bash
prefect work-pool inspect docker-pool

This will help me provide more specific guidance for your setup. The websocket errors in your logs suggest there might also be a connectivity issue between your worker and the Prefect server. Are you running Prefect in local mode or connected to Prefect Cloud?

Caio Henrique

07/21/2025, 1:55 AM

fatal: not a git repository (or any of the parent directories): .git same error

Caio Henrique

07/21/2025, 1:55 AM

@Marvin same error fatal: not a git repository (or any of the parent directories): .git

Marvin

07/21/2025, 1:55 AM

✅ thought for 19.9 seconds

Marvin

07/21/2025, 1:56 AM

This error occurs because the Docker container isn't properly set up to clone the Git repository. Let's fix this by modifying the deployment to ensure Git is available and the working directory is properly set up. Here's the corrected deployment script (

deployment.py

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python
from prefect import flow

@flow
def run_dlt_ingestion():
    pass

if __name__ == "__main__":
    run_dlt_ingestion.from_source(
        source="<https://github.com/caiohmb/mdsstack.git>",
        entrypoint="flows/flow.py:run_dlt_ingestion"
    ).deploy(
        name="ingestao-dlt-clima",
        work_pool_name="docker-pool",
        job_variables={
            "image": "prefecthq/prefect:2-python3.12-conda",  # This image includes git
            "volumes": ["/opt/prefect/flows:/opt/prefect/flows"],
            "env": {"PREFECT_LOGGING_LEVEL": "DEBUG"},  # Add more logging for debugging
        },
        push=False  # Ensure we're not trying to push to a registry
    )

Now, let's set up the work pool with the correct configuration: 1. Delete the existing work pool:

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bash
prefect work-pool delete docker-pool

2. Create a new Docker work pool with the correct base configuration:

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prefect work-pool create docker-pool --type docker

3. Update the work pool configuration. Create a file called `docker-pool-config.json`:

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json
{
    "job_configuration": {
        "image": "prefecthq/prefect:2-python3.12-conda",
        "pull_policy": "always",
        "auto_remove": true,
        "volumes": ["/opt/prefect/flows:/opt/prefect/flows"],
        "network_mode": "host"
    }
}

4. Apply the work pool configuration:

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prefect work-pool update docker-pool --base-job-template docker-pool-config.json

5. Delete the existing deployment:

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prefect deployment delete ingestao-dlt-clima/run_dlt_ingestion

6. Apply the new deployment:

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python deployment.py

7. Start a new worker:

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prefect worker start -p docker-pool

8. Test the deployment:

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prefect deployment run ingestao-dlt-clima/run_dlt_ingestion

If you're still seeing the git error, let's try an alternative approach using a custom Dockerfile. Create a file named `Dockerfile`:

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Dockerfile
FROM prefecthq/prefect:2-python3.12-conda

# Install git
RUN apt-get update && apt-get install -y git

# Set up working directory
WORKDIR /opt/prefect/flows

# Create directory for git operations
RUN mkdir -p /opt/prefect/flows && \
    chmod 777 /opt/prefect/flows

Build and use this custom image: 1. Build the custom image:

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docker build -t my-prefect-runner .

2. Update your deployment script to use the custom image:

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python
from prefect import flow

@flow
def run_dlt_ingestion():
    pass

if __name__ == "__main__":
    run_dlt_ingestion.from_source(
        source="<https://github.com/caiohmb/mdsstack.git>",
        entrypoint="flows/flow.py:run_dlt_ingestion"
    ).deploy(
        name="ingestao-dlt-clima",
        work_pool_name="docker-pool",
        job_variables={
            "image": "my-prefect-runner:latest",
            "volumes": ["/opt/prefect/flows:/opt/prefect/flows"],
            "env": {"PREFECT_LOGGING_LEVEL": "DEBUG"},
        }
    )

3. Apply the deployment again:

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bash
python deployment.py

Also, let's verify your actual flow structure. In your GitHub repository, the structure should be:

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mdsstack/
├── flows/
│   └── flow.py  # Contains your run_dlt_ingestion flow
└── deployment.py

And your

flows/flow.py

should contain:

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python
from prefect import flow

@flow
def run_dlt_ingestion():
    # Your actual flow code here
    print("Flow is running!")

if __name__ == "__main__":
    run_dlt_ingestion()

Could you confirm: 1. Is this the correct structure of your repository? 2. Are you running Prefect locally or using Prefect Cloud? 3. Can you share the output of

docker ps

when the worker is running? This will help me provide more specific guidance if the issue persists.

Caio Henrique

07/21/2025, 2:28 AM

@Marvin give me a custom dockerfile which install git to prefect 3

Marvin

07/21/2025, 2:29 AM

✅ thought for 19.7 seconds

Marvin

07/21/2025, 2:29 AM

Here's a custom Dockerfile for Prefect 3.x that includes Git and some common dependencies:

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Dockerfile
# Use the official Prefect 3.x base image
FROM prefecthq/prefect:2024.01-python3.11

# Switch to root to install packages
USER root

# Install git and other useful packages
RUN apt-get update && \
    apt-get install -y \
    git \
    curl \
    && rm -rf /var/lib/apt/lists/*

# Create and set permissions for the prefect directory
RUN mkdir -p /opt/prefect/flows && \
    chown -R prefect:prefect /opt/prefect && \
    chmod -R 777 /opt/prefect

# Set working directory
WORKDIR /opt/prefect/flows

# Switch back to prefect user
USER prefect

Let's build and use this image. Here are the steps: 1. Save the Dockerfile in your project directory 2. Build the Docker image:

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bash
docker build -t my-prefect-runner:3.0 .

3. Update your deployment script (

deployment.py

) to use this image:

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python
from prefect import flow

@flow
def run_dlt_ingestion():
    pass

if __name__ == "__main__":
    run_dlt_ingestion.from_source(
        source="<https://github.com/caiohmb/mdsstack.git>",
        entrypoint="flows/flow.py:run_dlt_ingestion"
    ).deploy(
        name="ingestao-dlt-clima",
        work_pool_name="docker-pool",
        job_variables={
            "image": "my-prefect-runner:3.0",
            "volumes": ["/opt/prefect/flows:/opt/prefect/flows"]
        }
    )

4. Create/update your Docker work pool:

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bash
prefect work-pool create docker-pool --type docker

5. Apply the deployment:

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bash
python deployment.py

6. Start the worker:

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bash
prefect worker start -p docker-pool

7. Test the deployment:

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bash
prefect deployment run ingestao-dlt-clima/run_dlt_ingestion

Some additional features you might want to add to the Dockerfile depending on your needs:

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Dockerfile
# Extended version with more tools and Python packages
FROM prefecthq/prefect:2024.01-python3.11

USER root

# Install system dependencies
RUN apt-get update && \
    apt-get install -y \
    git \
    curl \
    wget \
    jq \
    vim \
    && rm -rf /var/lib/apt/lists/*

# Install additional Python packages if needed
RUN pip install --no-cache-dir \
    pandas \
    requests \
    python-dotenv

# Create and set permissions for the prefect directory
RUN mkdir -p /opt/prefect/flows && \
    chown -R prefect:prefect /opt/prefect && \
    chmod -R 777 /opt/prefect

# Set working directory
WORKDIR /opt/prefect/flows

# Configure git (optional)
RUN git config --system --add safe.directory '*'

# Switch back to prefect user
USER prefect

Key points about this setup: 1. Uses the latest Prefect 3.x base image 2. Installs Git and other useful tools 3. Sets up proper permissions for the Prefect user 4. Configures a safe directory for Git operations 5. Includes common Python packages (in the extended version) If you need to add any specific dependencies for your flows, you can add them to the

pip install

command in the Dockerfile. To verify everything is working correctly after building and deploying, you can: 1. Check if the image was built successfully:

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bash
docker images | grep my-prefect-runner

2. Verify the worker is running:

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bash
prefect worker ls

3. Check deployment status:

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bash
prefect deployment ls

Let me know if you need any clarification or run into any issues!

Caio Henrique

07/21/2025, 1:14 PM

@Marvin File "/usr/local/lib/python3.12/site-packages/docker/errors.py", line 39, in create_api_error_from_http_exception raise cls(e, response=response, explanation=explanation) from e docker.errors.ImageNotFound: 404 Client Error for http+docker://localhost/v1.48/images/create?tag=latest&fromImage=prefect-git: Not Found ("pull access denied for prefect-git, repository does not exist or may require 'docker login': denied: requested access to the resource is denied") 131209.487 | INFO | prefect.flow_runs.worker - Reported flow run 'e6ddc434-5dae-4123-9871-fdb0ebf576c3' as crashed: Flow run could not be submitted to infrastructure: ImageNotFound(HTTPError('404 Client Error: Not Found for url: http+docker://localhost/v1.48/images/create?tag=latest&fromImage=prefect-git'))

Marvin

07/21/2025, 1:14 PM

✅ thought for 18.5 seconds

Marvin

07/21/2025, 1:14 PM

I see the error - it's trying to pull a non-existent image named "prefect-git". Let's fix your deployment configuration to use the correct image name that we built. 1. First, verify the image you built is available locally:

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bash
docker images

2. Update your deployment script (

deployment.py

) with the correct image name:

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python
from prefect import flow

@flow
def run_dlt_ingestion():
    pass

if __name__ == "__main__":
    run_dlt_ingestion.from_source(
        source="<https://github.com/caiohmb/mdsstack.git>",
        entrypoint="flows/flow.py:run_dlt_ingestion"
    ).deploy(
        name="ingestao-dlt-clima",
        work_pool_name="docker-pool",
        job_variables={
            "image": "my-prefect-runner:3.0",  # Make sure this matches the name you used in docker build
            "volumes": ["/opt/prefect/flows:/opt/prefect/flows"]
        }
    )

3. Make sure you've built the image first:

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bash
# Build the image with the correct name
docker build -t my-prefect-runner:3.0 .

4. Verify the work pool configuration:

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bash
prefect work-pool delete docker-pool
prefect work-pool create docker-pool --type docker

5. Apply the deployment again:

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bash
python deployment.py

6. Start a new worker:

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bash
prefect worker start -p docker-pool

If you're still seeing issues, let's try with an explicit work pool configuration. Create a file named `docker-pool-config.json`:

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json
{
    "job_configuration": {
        "image": "my-prefect-runner:3.0",
        "pull_policy": "if_not_present",
        "auto_remove": true,
        "volumes": ["/opt/prefect/flows:/opt/prefect/flows"]
    }
}

Then update the work pool:

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bash
prefect work-pool update docker-pool --base-job-template docker-pool-config.json

The key points to check: 1. Make sure the image name in your deployment matches exactly what you used in

docker build

2. Verify the image exists locally with

docker images

3. Set

pull_policy

to "if_not_present" to use local images Could you please: 1. Run

docker images

and share the output? 2. Confirm what name you used when building the Docker image? 3. Share the exact error message you get after making these changes? This will help me provide more specific guidance if you're still encountering issues.

Caio Henrique

07/21/2025, 1:17 PM

@Marvin help me to create a dockerfile with necessery to run

Marvin

07/21/2025, 1:17 PM

✅ thought for 22.8 seconds

Marvin

07/21/2025, 1:18 PM

I'll help you create a complete Dockerfile for your Prefect deployment. Let's build it step by step: 1. First, create a

Dockerfile

in your project directory:

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Dockerfile
# Use the latest Prefect 3.x base image
FROM prefecthq/prefect:2024.01-python3.11

# Switch to root to install packages
USER root

# Install system dependencies including git
RUN apt-get update && \
    apt-get install -y \
    git \
    curl \
    wget \
    && rm -rf /var/lib/apt/lists/*

# Create and set permissions for the prefect directory
RUN mkdir -p /opt/prefect/flows && \
    chown -R prefect:prefect /opt/prefect && \
    chmod -R 777 /opt/prefect

# Set working directory
WORKDIR /opt/prefect/flows

# Install Python dependencies (add your specific requirements here)
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# Configure git to allow operations in mounted directories
RUN git config --system --add safe.directory '*'

# Switch back to prefect user
USER prefect

2. Create a

requirements.txt

file in the same directory:

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text
pandas
requests
python-dotenv
# Add any other Python packages your flow needs

3. Build the Docker image:

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bash
docker build -t mds-prefect:latest .

4. Update your deployment script (

deployment.py

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python
from prefect import flow

@flow
def run_dlt_ingestion():
    pass

if __name__ == "__main__":
    run_dlt_ingestion.from_source(
        source="<https://github.com/caiohmb/mdsstack.git>",
        entrypoint="flows/flow.py:run_dlt_ingestion"
    ).deploy(
        name="ingestao-dlt-clima",
        work_pool_name="docker-pool",
        job_variables={
            "image": "mds-prefect:latest",
            "volumes": ["/opt/prefect/flows:/opt/prefect/flows"]
        }
    )

Now, let's set everything up step by step: 1. Create the directory structure:

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bash
mkdir -p mds-prefect
cd mds-prefect

2. Create all necessary files:

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bash
# Create Dockerfile
touch Dockerfile

# Create requirements.txt
touch requirements.txt

# Create deployment script
touch deployment.py

3. Build the image:

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bash
docker build -t mds-prefect:latest .

4. Verify the image was built:

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bash
docker images | grep mds-prefect

5. Set up the work pool:

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bash
# Remove existing work pool if it exists
prefect work-pool delete docker-pool

# Create new work pool
prefect work-pool create docker-pool --type docker

6. Apply the deployment:

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bash
python deployment.py

7. Start the worker:

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bash
prefect worker start -p docker-pool

Your directory structure should look like this:

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mds-prefect/
├── Dockerfile
├── requirements.txt
└── deployment.py

If you need additional packages or have specific dependencies, you can modify the

requirements.txt

file accordingly. To test everything: 1. First, verify the deployment was created:

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bash
prefect deployment ls

2. Run the deployment:

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bash
prefect deployment run ingestao-dlt-clima/run_dlt_ingestion

If you need to debug: 1. Check worker logs:

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bash
prefect worker ls

2. Check container logs:

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bash
docker ps  # Get the container ID
docker logs <container-id>

Let me know if you run into any issues or need clarification on any of these steps!

Caio Henrique

07/21/2025, 1:57 PM

@Marvin (venv) PS C:\opt\mds-test\mdsstack> docker run -it caiohmb/mds-prefect:latest /bin/bash docker: Error response from daemon: unable to find user prefect: no matching entries in passwd file Run 'docker run --help' for more information (venv) PS C:\opt\mds-test\mdsstack>

Marvin

07/21/2025, 1:57 PM

✅ thought for 17.0 seconds

Marvin

07/21/2025, 1:58 PM

The error occurs because the user 'prefect' isn't properly created in the Docker image. Let's fix the Dockerfile by adding the user creation step:

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Dockerfile
# Use the latest Prefect 3.x base image
FROM python:3.11-slim

# Install system dependencies
RUN apt-get update && \
    apt-get install -y \
    git \
    curl \
    wget \
    && rm -rf /var/lib/apt/lists/*

# Create prefect user and group
RUN groupadd -g 1000 prefect && \
    useradd -m -u 1000 -g prefect prefect

# Create and set permissions for the prefect directory
RUN mkdir -p /opt/prefect/flows && \
    chown -R prefect:prefect /opt/prefect && \
    chmod -R 777 /opt/prefect

# Install Prefect
RUN pip install -U prefect

# Set working directory
WORKDIR /opt/prefect/flows

# Install Python dependencies (add your specific requirements here)
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# Configure git to allow operations in mounted directories
RUN git config --system --add safe.directory '*'

# Switch to prefect user
USER prefect

# Command to keep container running
CMD ["bash"]

Now, let's rebuild and run: 1. Build the image:

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bash
docker build -t caiohmb/mds-prefect:latest .

2. Run the container:

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bash
docker run -it caiohmb/mds-prefect:latest /bin/bash

If you want to run without the prefect user (for testing purposes), you can use:

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bash
docker run -it --user root caiohmb/mds-prefect:latest /bin/bash

Make sure you have a

requirements.txt

file in the same directory as your Dockerfile with your Python dependencies:

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text
prefect>=2.14.0
pandas
requests
python-dotenv
# Add any other packages you need

After building the new image, update your deployment script (

deployment.py

Copy code

python
from prefect import flow

@flow
def run_dlt_ingestion():
    pass

if __name__ == "__main__":
    run_dlt_ingestion.from_source(
        source="<https://github.com/caiohmb/mdsstack.git>",
        entrypoint="flows/flow.py:run_dlt_ingestion"
    ).deploy(
        name="ingestao-dlt-clima",
        work_pool_name="docker-pool",
        job_variables={
            "image": "caiohmb/mds-prefect:latest",
            "volumes": ["/opt/prefect/flows:/opt/prefect/flows"]
        }
    )

Then: 1. Build the image:

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bash
docker build -t caiohmb/mds-prefect:latest .

2. Verify the image:

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bash
docker images

3. Test running the container:

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bash
docker run -it caiohmb/mds-prefect:latest /bin/bash

4. Update work pool:

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bash
prefect work-pool delete docker-pool
prefect work-pool create docker-pool --type docker

5. Deploy:

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bash
python deployment.py

6. Start worker:

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bash
prefect worker start -p docker-pool

This should resolve the user issue and give you a working Docker container for your Prefect flows. Let me know if you need any clarification or run into other issues!

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