< Marvin> I deploy flows from source in a docker container a Prefect Community #marvin-in-the-wild

<@ULVA73B9P> I deploy flows from source in a docke...

Philipp

06/11/2024, 1:13 PM

@Marvin I deploy flows from source in a docker container and it contains several modules. I get ModuleNotFoundError when one of the modules tries to import another one. The PYTHONPATH is set correctly so the modules can be found when trying to run it manually. It seems when prefect is respecting the PYTHONPATH when loading the flow code. How can I make this work?

Marvin

06/11/2024, 1:13 PM

It seems you're running into a

ModuleNotFoundError

when deploying flows in a Docker container, despite having the

PYTHONPATH

set correctly. Here's a summary of the problem and some steps you can take to resolve it: 1. Verify Source Path in Docker Image: Ensure the path containing your modules is included in the Docker image and that

PYTHONPATH

is set correctly within the Docker container context. 2. Use
requirements.txt
: While building your Docker image, make sure all necessary dependencies are listed in your

requirements.txt

and are installed during the Docker build process. 3. Consolidate Imports: Double-check your import statements to ensure you're using relative imports if needed. This is especially important within packages. 4. Testing Docker Container: Manually run a simple Python script within the Docker container to verify that modules can be imported properly. This isolates whether the issue is with Prefect or your Docker setup. 5. Docker and Prefect Block Configuration: Ensure that Prefect is configured correctly to respect your Docker image’s settings. Prefect's

DockerBlock

might be useful here. For deeper insight, check the following resources and examples: - Custom Docker Image for Prefect Flows - A GitHub issue discussing a similar problem: ModuleNotFoundError in deployed flows If these steps do not resolve your issue, consider running your modules as a package or using absolute imports for better results in Docker. Help me, help you.

Philipp

06/11/2024, 1:41 PM

@Marvin When using relative imports I get ModuleNotFoundError("No module named '__prefect_loader__.config'") for a module named config

Marvin

06/11/2024, 1:42 PM

It appears you're encountering a known issue with relative imports in Prefect cloud deployments, which leads to a

ModuleNotFoundError

for the module name

__prefect_loader__.config

. Here are potential workarounds and suggestions based on the gathered information: ### Workarounds: 1. Absolute Imports: Use absolute imports instead of relative imports. This approach avoids issues related to how Prefect packages and loads modules.

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python
   # In submodule.py
   from prefect import task

   @task
   def repeatable_task():
       from prefect import get_run_logger
       logger = get_run_logger()
       <http://logger.info|logger.info>('Doing some task now')

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python
   # In workflow.py
   from prefect import flow
   from my_package.submodule import repeatable_task

   @flow
   def top_level_flow():
       repeatable_task()

2. Local package installation: Convert your project directory into a package and install it in the Docker image using

pip

. Ensure your project is structured as a package with an

__init__.py

file.

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Dockerfile
   # Dockerfile
   COPY . /app
   WORKDIR /app
   RUN pip install -e .

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bash
   # In deployment.py or via CLI
   pip install -e .

### Documentation and Issues: - Style Guide for Imports: Prefect suggests a structured approach to imports that avoids relative imports for clarity and reliability. - Prefect Import Style Guide - Related GitHub Issues: - ModuleNotFoundError with `__prefect_loader__` - Local relative imports do not work in flows/tasks - No module named `__prefect_loader__` when using `load_flow_from_script` Refer to these resources to adjust your code structure and deployment strategy to avoid the import errors. Let's hope this helps your modules find their way around!

Philipp

06/11/2024, 2:24 PM

@Marvin doing it with absolute imports as in 1.) I get ModuleNotFoundError("No module named 'my_package'"). Can you show me the directory structure of the workflow.py , the module and the submodule?

Marvin

06/11/2024, 2:24 PM

Certainly! Below is an example of a directory structure with

workflow.py

submodule.py

, and

__init__.py

files to ensure proper module recognition. This structure follows the absolute import strategy. ### Directory Structure

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my_project/
├── my_package/
│   ├── __init__.py
│   ├── submodule.py
│   └── workflow.py
├── requirements.txt
└── Dockerfile

### my_package/__init__.py This file can be empty or used to initialize your package.

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python
# my_package/__init__.py
# This file can be empty

### my_package/submodule.py Define your task here.

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python
# my_package/submodule.py
from prefect import task

@task
def repeatable_task():
    from prefect import get_run_logger
    logger = get_run_logger()
    <http://logger.info|logger.info>('Doing some task now')

### my_package/workflow.py Import and use your tasks here.

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python
# my_package/workflow.py
from prefect import flow
from my_package.submodule import repeatable_task  # Absolute import

@flow
def top_level_flow():
    repeatable_task()

if __name__ == '__main__':
    top_level_flow()

### Dockerfile Build your Docker image to include the package.

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Dockerfile
# Dockerfile
FROM python:3.8-slim

WORKDIR /app

# Install Prefect
RUN pip install prefect

# Copy the whole project to the container
COPY . /app

# Install the package as an editable module
RUN pip install -e .

# Set the PYTHONPATH (if needed)
ENV PYTHONPATH "${PYTHONPATH}:/app"

CMD ["python", "my_package/workflow.py"]

### requirements.txt List your dependencies here.

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plaintext
prefect

### Steps to Deploy 1. Build Docker Image:

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sh
   docker build -t my_prefect_image .

2. Run Docker Container:

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sh
   docker run my_prefect_image

3. Deploy with Prefect: Ensure you follow relevant documentation to deploy using Prefect's CLI or Python API, passing the correct flow and deployment parameters. This structure ensures that your package

my_package

is recognized correctly, even when using absolute imports within a Docker container.

Philipp

06/11/2024, 2:35 PM

@Marvin How would it look when deploying from source using a github repo?

Marvin

06/11/2024, 2:36 PM

Deploying from source using a GitHub repository involves slightly different steps, but the overall directory structure and code setup remain largely the same. Here is how you can set up and deploy from a GitHub repository using Prefect. ### Directory Structure Ensure your repository has the necessary structure:

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my_repo/
├── my_package/
│   ├── __init__.py
│   ├── submodule.py
│   └── workflow.py
├── requirements.txt
└── Dockerfile

### Deployment Steps 1. Create GitHub Repository: Push your project structure to a GitHub repository, for example,

<https://github.com/yourusername/my_repo>

. 2. Define Workflow and Tasks: Use the same

workflow.py

and

submodule.py

as shown earlier. 3. Dockerfile: Ensure your Dockerfile is set up to copy and install your package.

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Dockerfile
   # Dockerfile
   FROM python:3.8-slim

   WORKDIR /app

   # Install Prefect
   RUN pip install prefect

   # Clone the repository
   RUN apt-get update && apt-get install -y git
   RUN git clone <https://github.com/yourusername/my_repo.git> /app

   # Install the package as an editable module
   RUN pip install -e /app

   # Set the PYTHONPATH (if needed)
   ENV PYTHONPATH "${PYTHONPATH}:/app"

   CMD ["python", "my_package/workflow.py"]

4. Push Changes to GitHub: Ensure all your files, including the

Dockerfile

, are pushed to the repository. 5. Create Prefect Deployment: Use the Prefect CLI or Python API to create a deployment from the source. Example using Prefect CLI:

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sh
   prefect deployment build my_package/workflow.py:top_level_flow -n my-flow -q default -sb github/yourusername/my_repo -ib docker-container/your-docker-block

6. Register Deployment: Apply the deployment to make it available in Prefect Cloud.

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sh
   prefect deployment apply my-flow-deployment.yaml

7. Run the Flow: Trigger the flow run from the Prefect UI or using the CLI:

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sh
   prefect deployment run my-flow/top_level_flow

### Example of Deployment YAML When you build your deployment, it will generate a YAML file, which could look something like this:

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yaml
name: my-flow
work_pool:
  name: default
flow_name: top_level_flow
work_queue_name: default
flow_location: /app/my_package/workflow.py
storage:
  module: "prefect.filesystems"
  class: "GitHub"
  settings:
    repository: "yourusername/my_repo"
infrastructure:
  type: "docker"
  image: "your-docker-registry/your-image:latest"

### Using Prefect API for Deployment Alternatively, here is an example using the Prefect Python API:

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python
from prefect.deployments import Deployment
from prefect.filesystems import GitHub
from prefect.infrastructure.docker import DockerContainer
from my_package.workflow import top_level_flow

# Define storage
github_block = GitHub(repository="<https://github.com/yourusername/my_repo>")

# Define infrastructure
docker_container_block = DockerContainer(
    image="your-docker-registry/your-image:latest"
)

# Create deployment
deployment = Deployment.build_from_flow(
    flow=top_level_flow,
    name="my-flow",
    storage=github_block,
    infra_overrides=docker_container_block,
    work_queue_name="default"
)

# Apply the deployment
deployment.apply()

Ensure you replace

yourusername

my_repo

, and other placeholders with your actual GitHub username, repository name, and Docker registry details. This should help you set up and deploy your Prefect flow from a GitHub repository.

Philipp

06/11/2024, 3:32 PM

@Marvin How do I set the working directory of a flow?

Philipp

06/11/2024, 5:34 PM

@Marvin it seems that it does not work if my_package is not at the top level of the repository. How can I change the working directory where the flow is executed from?

Marvin

06/11/2024, 5:35 PM

To ensure that the working directory is correctly set during the execution of your flow, particularly when your project is not located at the top level of the repository, you can explicitly set the working directory in your deployment configuration. Here is a detailed guide for doing this: ### Directory Structure Example structure with nested

my_package

directory:

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my_repo/
├── src/
│   └── my_package/
│       ├── __init__.py
│       ├── submodule.py
│       └── workflow.py
├── requirements.txt
└── Dockerfile

### Configuration 1. Update
prefect.yaml
: Make sure your

prefect.yaml

file is correctly using the

set_working_directory

step to change the working directory to

/app/src

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yaml
   name: my-prefect-project
   prefect-version: 2.x.y
   
   # Deployments section for providing configurations
   deployments:
     - name: my-deployment
       entrypoint: my_package/workflow.py:top_level_flow
       work_pool_name: my-work-pool
       job_variables:
         image: my-docker-image:latest
       storage:
         module: prefect.filesystems
         class: GitHub
         settings:
           repository: yourusername/my_repo
       pull_steps:
         - prefect.deployments.steps.set_working_directory:
             directory: /app/src  # Ensure this points to the correct directory inside the Docker container

2. Update Dockerfile: Ensure the Dockerfile copies the repository to the correct directory and installs the package from there.

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Dockerfile
   # Dockerfile
   FROM python:3.8-slim

   WORKDIR /app

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

   # Install Prefect
   RUN pip install prefect

   # Clone the repository
   RUN git clone <https://github.com/yourusername/my_repo.git> /app

   # Change to the directory that contains your package
   WORKDIR /app/src

   # Install the package as an editable module
   RUN pip install -e .

   CMD ["python", "my_package/workflow.py"]

### Deployment Using CLI After configuring the `prefect.yaml`:

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sh
prefect deployment build src/my_package/workflow.py:top_level_flow -n my-deployment -q default -sb github/yourusername/my_repo -ib docker-container/my-docker-block
prefect deployment apply my-deployment-deployment.yaml

### Example Project for Workflow and Tasks The code remains the same as before, except ensure that your imports correctly reference the package location. #### src/my_package/__init__.py

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python
# src/my_package/__init__.py
# This file can be empty

#### src/my_package/submodule.py

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python
# src/my_package/submodule.py
from prefect import task

@task
def repeatable_task():
    from prefect import get_run_logger
    logger = get_run_logger()
    <http://logger.info|logger.info>('Doing some task now')

#### src/my_package/workflow.py

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python
# src/my_package/workflow.py
from prefect import flow
from my_package.submodule import repeatable_task  # Absolute import

@flow
def top_level_flow():
    repeatable_task()

if __name__ == '__main__':
    top_level_flow()

### Running the Deployment 1. Build Docker Image:

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sh
   docker build -t my_prefect_image .

2. Push Docker Image to your Docker registry if needed. 3. Run the Flows: Trigger or schedule the flow runs from either the Prefect UI or CLI. By setting the working directory explicitly in both the Dockerfile and the Prefect deployment configuration, you can ensure that Prefect runs the flow in the correct directory, even if your package is nested within the repository.

Philipp

06/12/2024, 9:15 AM

@Marvin Doesn't set_working_directory set the directory where the git repository is pulled into instead of the directory where the flows are executed? This is not working as you described

Marvin

06/12/2024, 9:15 AM

You are correct. The

set_working_directory

step in Prefect is used to set the directory where the repository is pulled into, not necessarily the directory from which the flows are executed. To properly set the working directory for the execution of flows, you would typically need to adjust your infrastructure and deployment settings. Given this clarification, here’s how you can explicitly set the working directory for your flow execution: ### Directory Structure

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my_repo/
├── src/
│   └── my_package/
│       ├── __init__.py
│       ├── submodule.py
│       └── workflow.py
├── requirements.txt
└── Dockerfile

### Docker Configuration Update your Dockerfile to ensure your working directory is set appropriately within the container:

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Dockerfile
# Dockerfile
FROM python:3.8-slim

# Set the working directory to /app/src
WORKDIR /app/src

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

# Install Prefect
RUN pip install prefect

# Clone the repository to /app
RUN git clone <https://github.com/yourusername/my_repo.git> /app

# Ensure we are in the /app/src directory
WORKDIR /app/src

# Install the package as an editable module
RUN pip install -e .

# Set the command to run the workflow
CMD ["python", "my_package/workflow.py"]

### Prefect Deployment Configuration In your

prefect.yaml

, you’ll not only configure the storage but also ensure that the entrypoint is correctly specified.

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yaml
name: my-prefect-project
prefect-version: 2.x.y

deployments:
  - name: my-deployment
    entrypoint: src/my_package/workflow.py:top_level_flow
    work_pool_name: my-work-pool
    job_variables:
      image: my-docker-image:latest
    storage:
      module: prefect.filesystems
      class: GitHub
      settings:
        repository: yourusername/my_repo
    pull_steps:
      - prefect.deployments.steps.set_working_directory:
          directory: /app/src

### Adjusting Deployment Using CLI When deploying from source using the CLI, make sure to set the appropriate paths and configurations:

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sh
# Building the deployment
prefect deployment build src/my_package/workflow.py:top_level_flow -n my-deployment -q default -sb github/yourusername/my_repo -ib docker-container/my-docker-block

# Apply the deployment
prefect deployment apply my-deployment-deployment.yaml

### Example Flow and Tasks Here's the code structure again for completeness: #### src/my_package/__init__.py

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python
# src/my_package/__init__.py
# This file can be empty

#### src/my_package/submodule.py

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python
# src/my_package/submodule.py
from prefect import task

@task
def repeatable_task():
    from prefect import get_run_logger
    logger = get_run_logger()
    <http://logger.info|logger.info>('Doing some task now')

#### src/my_package/workflow.py

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python
# src/my_package/workflow.py
from prefect import flow
from my_package.submodule import repeatable_task  # Absolute import

@flow
def top_level_flow():
    repeatable_task()

if __name__ == '__main__':
    top_level_flow()

### Running the Deployment 1. Build and Push Docker Image:

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sh
   docker build -t my_prefect_image .
   docker push my_prefect_image

2. Deploy the Flow: Deploying the flow using the CLI commands provided above ensures that the flow entrypoint and job variables are properly configured. 3. Run the Flow: Trigger the flow run from the Prefect UI or CLI:

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sh
   prefect deployment run my-prefect-project/my-deployment

This setup ensures that when your flow runs, it runs within the

/app/src

directory, where your code and dependencies are appropriately installed and available.

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