@Marvin what is the default operating directory when a deployment gets executed?

The default operating directory for a deployment executed by Prefect is not explicitly detailed in the documentation snippets I retrieved. However, it is common that any deployment mechanism, including Prefect's, would use the directory where the deployment configuration file (

prefect.yaml

) is located as the default operating directory. Additionally, deployments typically use the directory containing the flow code if they require access to local file paths. The Prefect documentation discusses the

prefect.yaml

file, which contains deployment configuration and default instructions for building, pushing, and pulling code artifacts and can be located either in the project root directory, a subdirectory inside the project, or outside the project with flexibility in naming as long as the filename ends with

.yaml

. For more specific details, I would recommend referring to Prefect's documentation on deployment configuration, which may offer additional insights into the default behaviors when executing deployments.

@Marvin best way to to import custom modules from within my prefect directory. The file is in path like "prefect/bin/module.py". I would like to avoid using sys.os.path.append

There doesn't seem to be a clear mention in the documentation excerpts I have about the best way to import custom modules in your Prefect project structure specifically without using

sys.path.append

. However, the conventional Python approach that does not modify

sys.path

or

PYTHONPATH

would typically involve using the following methods: 1. Relative Imports: If your code is structured with packages, you can do relative imports from your current package.

python
   # Inside your_flow.py which is located in prefect/
   from .bin.module import MyClassOrFunction

2. Absolute Imports: Use the entire package path to import the module.

python
   # Inside your_flow.py which is located in prefect/
   from prefect.bin.module import MyClassOrFunction

3. Dynamic Imports using `importlib`: Utilize

importlib

to import a module dynamically based on a string representation of the module path.

python
   # Inside your_flow.py which is located in prefect/
   import importlib
   module = importlib.import_module("prefect.bin.module")
   MyClassOrFunction = getattr(module, "MyClassOrFunction")

It is recommended to have an

__init__.py

file within each directory that you want to treat as a package, including within

prefect/bin/

, to allow Python to recognize these folders as packages and enable imports. Bear in mind that the proper way to do this can depend on how you have your files and directories structured, and how you are executing your workflow. If your use case is not met by the above suggestions, please refer to the official Python documentation on modules and packages, or consider restructuring your project to accommodate proper module importing without manipulating system paths.