< Marvin> I have this flow source code Why am I getting the Prefect Community #marvin-in-the-wild

<@ULVA73B9P> I have this flow source code. Why am ...

Joshua Caskie

06/25/2024, 12:36 PM

@Marvin I have this flow source code. Why am I getting the following error? Code:

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flow.from_source(
    source=GitRepository(
      url="my/git/repo.git",
      branch="develop",
      credentials=GitLabCredentials.load("repo-prefect")
    ),
    entrypoint="main.py:main"
  ).deploy(
    name="repo-deploy",
    work_pool_name="my-docker-pool",
    cron="0 0 * * *",
    tags=["dev", "repo"],
    build=False,
    job_variables={"env": {"EXTRA_PIP_PACKAGES": "pandas"} }
  )

Error:

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prefect.exceptions.ScriptError: Script at '/var/folders/bv/yzk7hd_d19s1c6n0krxwyr340000gq/T/tmp418livpe/repo-develop/main.py' encountered an exception: ModuleNotFoundError("No module named 'pandas._config'")

Marvin

06/25/2024, 12:36 PM

It appears the error you're encountering is due to the

pandas

module not being found. This can be related to several potential issues: 1. Dependencies Not Installed: The Docker image or environment where the flow is executing might not have the

pandas

library installed, or it failed to install properly. 2. Misconfigured Environment: The

EXTRA_PIP_PACKAGES

environment variable is supposed to install

pandas

, but it might not be working as intended. 3. Simultaneous Execution: There are known issues where flows using certain packages, such as

dbt

, can encounter

ModuleNotFoundError

when run concurrently. While this doesn’t directly mention

pandas

, it signals a potential problem with package management in concurrent executions. Steps to Troubleshoot and Fix: 1. Ensure Dependencies Are Installed: Ensure that the Docker image has

pandas

installed. You can add a requirements file or explicitly install it in your Dockerfile. 2. Verify Environment Variable Configuration: Make sure the syntax and method you’re using to set

EXTRA_PIP_PACKAGES

is correct and effective. 3. Isolation of Dependencies: Ensure that dependencies are isolated correctly or not interfered with other flows. Use virtual environments if needed. 4. Log Outputs for Debugging: - Check logs for messages about package installation failure. - Ensure Python and pip are at compatible versions. ### Example Dockerfile Addition

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dockerfile
FROM prefecthq/prefect:2-latest
RUN pip install pandas

### Prefect Deployment YAML Example Ensure your

prefect.yaml

file correctly configures environment and dependencies:

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yaml
deployments:
  - name: repo-deploy
    work_pool_name: my-docker-pool
    cron: "0 0 * * *"
    entrypoint: "main.py:main"
    parameters: {}
    tags: ["dev", "repo"]
    build: false
    job_variables:
      env:
        EXTRA_PIP_PACKAGES: "pandas"

### Sources - Issue with Simultaneous Running Deployed Flows - ScriptError when Dependencies Fail to Install - GitHub Repository Integration with Prefect By addressing these areas, you should be able to resolve the

ModuleNotFoundError

and ensure your flow runs smoothly.

Joshua Caskie

06/25/2024, 12:49 PM

@Marvin not sure if that's exactly it. Should I be specifying the

image

parameter of

flow.deploy()

with an image that has pandas installed? Or should I leave it blank and let Prefect build and name it?

Marvin

06/25/2024, 12:49 PM

To ensure that

pandas

or any other dependencies are available during the execution of your flow, you should specify the

image

parameter in your

flow.deploy()

method with a pre-built Docker image that contains these dependencies, such as

pandas

. ### Option 1: Specifying a Custom Docker Image You can create a Docker image that includes all necessary dependencies and specify it in the

image

parameter. This ensures that all required libraries are present when the flow runs. ### Example 1. Create Dockerfile:

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dockerfile
    FROM prefecthq/prefect:2-latest
    RUN pip install pandas

2. Build and Push Docker Image:

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sh
    docker build -t my-repo/my-image:my-tag .
    docker push my-repo/my-image:my-tag

3. Deploy Flow Using Custom Image:

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python
    from prefect import flow
    from prefect.deployments import Deployment

    git_repo = GitRepository(
        url="my/git/repo.git",
        branch="develop",
        credentials=GitLabCredentials.load("repo-prefect")
    )

    deployment = Deployment(
        flow=flow.from_source(
            source=git_repo,
            entrypoint="main.py:main"
        ),
        name="repo-deploy",
        work_pool_name="my-docker-pool",
        cron="0 0 * * *",
        image="my-repo/my-image:my-tag",
        tags=["dev", "repo"],
        job_variables={"env": {"EXTRA_PIP_PACKAGES": "pandas"} },
        build=False
    )
    deployment.deploy()

### Option 2: Allow Prefect to Build the Image If you prefer to let Prefect handle the image building, ensure that a

requirements.txt

file with

pandas

listed is present in your repository, and Prefect will include it in the Docker build. ### Example 1. Add
requirements.txt
to Your Repo:

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txt
    pandas

2. Deploy Flow Without Specifying Image:

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python
    from prefect import flow
    from prefect.deployments import Deployment

    git_repo = GitRepository(
        url="my/git/repo.git",
        branch="develop",
        credentials=GitLabCredentials.load("repo-prefect")
    )

    deployment = Deployment(
        flow=flow.from_source(
            source=git_repo,
            entrypoint="main.py:main"
        ),
        name="repo-deploy",
        work_pool_name="my-docker-pool",
        cron="0 0 * * *",
        tags=["dev", "repo"],
        job_variables={"env": {"EXTRA_PIP_PACKAGES": "pandas"} },
        build=True  # Set to True to build image with dependencies
    )
    deployment.deploy()

### Conclusion Specifying a custom Docker image ensures that your dependencies are reliably included. Otherwise, if you rely on Prefect’s automated build process, ensure your repository has the proper

requirements.txt

. ### Sources - Prefect Deployment Guide By following these steps, you should resolve the

ModuleNotFoundError

and ensure your flow runs with all required dependencies.

Joshua Caskie

06/25/2024, 12:52 PM

@Marvin I'm still getting the error with option 2. My repo has a requirements.txt with pandas in it, at the branch

develop

. I have

build=True

in the

flow.from_source().deploy()

method call. What else might it be?

Marvin

06/25/2024, 12:52 PM

It seems you're still encountering the

ModuleNotFoundError

for

pandas

, even when letting Prefect build the image. Here are a few additional steps and considerations to ensure the environment is correctly set up. ### Verify Docker Build Process Ensure the Docker build process is properly incorporating your

requirements.txt

. 1. Check Docker Build Logs: Verify that during the Docker build process,

pandas

is being installed without errors. The logs should show something like:

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Collecting pandas
    Downloading pandas-1.3.3.tar.gz (4.7 MB)

2. Validate Docker Image: After Prefect builds the Docker image, verify the image has

pandas

installed by running a container from the built image. ### Using Prefect's Custom Build Steps Ensure you are following Prefect's recommended practices for custom build steps. ### Example Prefect YAML Configuration Your

prefect.yaml

should correctly specify the Docker build parameters. Here's an example:

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yaml
name: repo-deploy
description: A deployment configuration for the repo flow.
work_pool:
  name: my-docker-pool
schedule:
  cron: "0 0 * * *"
tags:
  - dev
  - repo
storage:
  - type: prefect_docker.deployments.steps.build_docker_image
    requires: prefect-docker>=0.3.0
    image_name: my-repo/my-image
    tag: my-tag
    dockerfile: auto
    push: true
job:
  env: 
    EXTRA_PIP_PACKAGES: "pandas"

### Explicitly Specify Dependencies Add a

custom_dockerfile

to ensure dependencies are explicitly included during the build process. This might help in certain edge cases where the automated process fails.

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yaml
name: repo-deploy
description: A deployment configuration for the repo flow.
work_pool:
  name: my-docker-pool
schedule:
  cron: "0 0 * * *"
tags:
  - dev
  - repo
storage:
  - type: prefect_docker.deployments.steps.build_docker_image
    requires: prefect-docker>=0.3.0
    image_name: my-repo/my-image
    tag: my-tag
    dockerfile: ./Dockerfile
    push: true
job:
  env: 
    EXTRA_PIP_PACKAGES: "pandas"
.build:
  steps:
    - prefect_docker.deployments.steps.build_docker_image:
        image_name: my-repo/my-image
        tag: my-tag
        dockerfile: "./Dockerfile"
        push: true

### Example Dockerfile Ensure your

Dockerfile

is correctly set up in the repository (if not using the auto build):

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dockerfile
FROM prefecthq/prefect:2-latest
COPY requirements.txt .
RUN pip install -r requirements.txt

### Conclusion - Verify Docker Build Logs: Ensure

pandas

is installed without errors. - Inspect Built Image: Validate that the built Docker image contains

pandas

. - Customize Docker Build Steps: Use explicit build steps and configurations in

prefect.yaml

. By ensuring these steps, you should resolve dependency issues and ensure

pandas

is included in your Prefect flow execution environment. If problems persist, please share any additional error logs or details for more precise assistance.

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