tf-vars-to-pydantic 0.1.2

Features

• 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

Requirements

• Python ^3.11
• Pydantic ^1.10.x
• python-hcl2 ^4.3.x

Installation

You can install Tf Vars To Pydantic via [pip] from [PyPI]:

pip install tf-vars-to-pydantic

Usage

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

Contributing

Contributions are very welcome. To learn more, see the Contributor Guide.

License

Distributed under the terms of the MIT license, Tf Vars To Pydantic is free and open source software.

Issues

If you encounter any problems, please [file an issue] along with a detailed description.

Contributors

Andrew 💻 ⚠️ 📖