Hi everyone! I want to separate my GCP cloud resources by categories. I use pulumi's

gcp-python

. For instance, I want to store my buckets definitions in a separate directory or in python terms, simply in a separate python package, instances in another one, vpn and network definition in yet another one, and so on. With the directory structure below, I managed to import packages' code into pulumi's

__main__.py

and make it work. Nevertheless, I don't like that I have to do import statements

import pulumi
from pulumi_gcp import storage

both in a package module and in

__main__.py

itself. I know that am probably doing this wrong, so my question is: What is the best practice to separate pulumi resources as python packages? I would really appreciate some examples of how some of you do that. tree structure:

(pulumi_venv) some_user@MAC-C02YG37SJGH some-pulumi (master) $ tree
.
├── Pulumi.dev.yaml
├── Pulumi.yaml
├── __main__.py
├── __pycache__
│   └── __main__.cpython-37.pyc
├── buckets
│   ├── __init.py__
│   ├── __pycache__
│   │   ├── bucket_func.cpython-37.pyc
│   │   └── bucket_plain.cpython-37.pyc
│   ├── bucket_func.py
│   └── bucket_plain.py
└── requirements.txt

3 directories, 10 files

buckets/bucket_func.py which has a bucket creation within a function:

import pulumi
from pulumi_gcp import storage


def create_bucket5():
    # Create a GCP resource (Storage Bucket)
    bucket = storage.Bucket('pulumi-test-bucket-5', name="pulumi-test-bucket-5")

    # Export the DNS name of the bucket
    pulumi.export('bucket_name',  bucket.url)

buckets/bucket_plain.py which is a plain code file not wrapped into a function or something:

import pulumi
from pulumi_gcp import storage

# Create a GCP resource (Storage Bucket)
bucket = storage.Bucket('pulumi-test-bucket-5', name="pulumi-test-bucket-5")

# Export the DNS name of the bucket
pulumi.export('bucket_name',  bucket.url)

and the main.py for the buckets/bucket_func

import pulumi
from pulumi_gcp import storage

-->>import buckets.bucket_func

# State bucket
# Create a GCP resource (Storage Bucket)
bucket1 = storage.Bucket('pulumi-test-bucket-2')

# Export the DNS name of the bucket
pulumi.export('bucket_name',  bucket1.url)

-->>buckets.bucket_func.create_bucket5()

and also the main.py for the second case buckets/bucket_plain:

import pulumi
from pulumi_gcp import storage

-->>import buckets.bucket_plain

# State bucket
# Create a GCP resource (Storage Bucket)
bucket1 = storage.Bucket('pulumi-test-bucket-2')

# Export the DNS name of the bucket
pulumi.export('bucket_name',  bucket1.url)

In both cases it works and creates a

pulumi-test-bucket-5

bucket. Please note the

pulumi-test-bucket-2

in

__main__.py

is just a state bucket for pulumi.

(pulumi_venv) some_user@MAC-C02YG37SJGH some-pulumi (master) $ pulumi up
Enter your passphrase to unlock config/secrets
    (set PULUMI_CONFIG_PASSPHRASE to remember):
Previewing update (dev):

     Type                   Name                  Plan
     pulumi:pulumi:Stack    lodgify-pulumi-dev
 +   └─ gcp:storage:Bucket  pulumi-test-bucket-5  create

Resources:
    + 1 to create
    2 unchanged

Do you want to perform this update?
  yes
> no
  details

Hi dz, I believe your best bet is to create a master project, then multiple stacks within that project

thank you for the reply

Ah, I see now. Apologies, I misunderstood the question

ok, thank you @numerous-easter-93888. Let's hope that someone else will reply as well )