- Read a Terraform Variables HCL file (variables.tf) and create a Pydantic model from it
- Interpret complex data types (list(string), etc) into Python data types
- Interpret object data types into sub models
- Does not currently support terraform input validation
- Python ^3.11
- Pydantic ^1.10.x
- python-hcl2 ^4.3.x
You can install Tf Vars To Pydantic via [pip] from [PyPI]:
pip install tf-vars-to-pydantic
Assuming you have a tf vars file that looks like:
variable "foo" {
description = "String variable"
type = string
}
variable "bar" {
description = "String variable with default"
type = number
}
variable "baz" {
type = list(string)
}
variable "qux" {
description = "Boolean variable"
default = true
type = bool
}
from tf_vars_to_pydantic import convert_file
TFVarsModel = convert_file(path="./tests/fixtures/simple.tf", model_name="TFVarsModel")
tfvars_as_pydantic = TFVarsModel(foo="test", bar=7.2, baz=['boop', 'bing', 'bong'])
print(tfvars_as_pydantic)
# foo='test' bar=7.2 baz=['boop', 'bing', 'bong'] qux=True
Contributions are very welcome. To learn more, see the Contributor Guide.
Distributed under the terms of the MIT license, Tf Vars To Pydantic is free and open source software.
If you encounter any problems, please [file an issue] along with a detailed description.
Andrew 💻 |