How to load a file to Resources directory and have available at run time

Hi @clayms
,

I'm able to access a file that I uploaded to the resources directory of a code env, as shown below:

Initialization script:

## Base imports
from dataiku.code_env_resources import clear_all_env_vars
from dataiku.code_env_resources import set_env_path
from dataiku.code_env_resources import set_env_var

# Clears all environment variables defined by previously run script
clear_all_env_vars()

# Set the path to the cert file
set_env_path("MY_CERT_PATH", "cert/cert.crt")

I can then access the cert using the following code in a notebook with the kernel set to my code env:

import os

cert_path = os.environ["MY_CERT_PATH"]
print("cert_path:", cert_path)

with open(cert_path, "r") as file:
    print(file.read())

Could you please double check that the path to the file is correct? For example, in my above test, the cert is located in a subdirectory called "cert", so I set the relative path to "cert/cert.crt".

Please also make sure that you've updated the code env after changing the init script and uploading the file. If you're trying to access the cert from a notebook, please also make sure that you've restarted the kernel after updating the code env.

Additionally, per our documentation, please make sure that your code env meets the following requirements:

• Code environment resources require the core packages to be installed.
• Code environment resources are not supported on external conda code environments.
• Code environment resources are not made available to Spark executors.

If you're still not able to get it working, please provide provide the following information:

• A screenshot of the Resources tab of your code env similar to my screenshot above.
• The code that you're using to access the cert file, as well as the error message you're getting.
• How you're accessing the resources script. For example, are you accessing it from a Python recipe, or a notebook?
• Are you using containerized execution, or is your Python code running locally?

Thanks,

Zach