Based on the research, I can help you correct your code. The main issues are: 1. You're using the deprecated

GitRepository

storage method 2. The pandas installation needs to be handled differently Here's the corrected version of your code:

python
from prefect import flow

@flow
def flow1():
    import pandas as pd
    # your flow code here

# Deploy the flow directly from GitHub
flow1.from_source(
    source="<https://github.com/sabiagents/flows.git>",
    entrypoint="flow2.py:flow1",
).deploy(
    name="flow1",
    work_pool_name="default",
    job_variables={
        "env": {
            "EXTRA_PIP_PACKAGES": "pandas"
        }
    }
)

Key changes made: 1. Removed the deprecated

GitRepository

and

Secret

imports 2. Simplified the GitHub source specification to use a direct URL 3. Maintained your pandas installation through

EXTRA_PIP_PACKAGES

Additionally, you might want to consider creating a

requirements.txt

file in your repository with your dependencies listed. This is often a more maintainable approach. Your

requirements.txt

would look like:

pandas

Then you could modify your deployment to use this file:

python
flow1.from_source(
    source="<https://github.com/sabiagents/flows.git>",
    entrypoint="flow2.py:flow1",
).deploy(
    name="flow1",
    work_pool_name="default",
    job_variables={
        "env": {
            "EXTRA_PIP_PACKAGES": "-r requirements.txt"
        }
    }
)

This approach is more scalable as you can manage all your dependencies in one file. Let me know if you need any clarification or run into other issues!