conjector 1.8.0

Config injector for Python

Python Config Injector

What is this

It is a simple library to inject non-sensitive configurations into class variables. Basically, it's like BaseSettings in pydantic library but for constants in json, yaml, toml or ini formats. conjector can work with different Python types (like tuple, datetime, dataclass and so on) and recursively cast config values to them.

More information about the library and all features you can find in the official documentation.

When to use

• If you deal with constants in your code, like error messages, default values for something, numeric coefficients, and so on.
• If you hate global variables, and you like non-python files to store static information.
• If you want to have an easy way to manage different constants depending on environments (like test, dev, prod).
• If you like type hints and clean code.

How to install

To install this library just enter:

pip install conjector

By default, conjector work only with the builtin json and ini deserializers. To work with yaml or toml (if you are using python <= 3.10):

pip install conjector[yaml]
# or
pip install conjector[toml]
# or faster version of json
pip install conjector[json]

How to use

For injecting values you need only the decorator properties under a target class. By default, the library will search a config file application.yml in the same directory where your file with the used decorator is located, like below:

project_root
|---services
|   |   email_message_service.py
|   |   application.yml
|.....

Example:

services/application.yml:

default_text_style:
  size: 14
  weight: bold
  font: "Times New Roman"
  color:
    - 128
    - 128
    - 128
language_greetings:
  - language: english
    text: hello
  - language: german
    text: hallo
  - language: french
    text: bonjour
wellcome_message: "{greeting}! Thank you for registration, {username}!"
mailing_frequency:
  days: 5
  hours: 12

services/email_message_service.py:

from typing import TypedDict
from dataclasses import dataclass
from datetime import timedelta
from conjector import properties


@dataclass
class TextStyle:
    size: int
    weight: str
    font: str
    color: tuple[int, int, int] | str


class GreetingDict(TypedDict):
    language: str
    text: str


@properties
class EmailMessageService:
    default_text_style: TextStyle
    language_greetings: list[GreetingDict]
    wellcome_message: str
    mailing_frequency: timedelta | None

    # And using these class variables in some methods...

And that's how will look an equivalent of the code above but with "hard-coded" constants, without config files and @properties decorator:

class EmailMessageService:
    default_text_style = TextStyle(
        size=14, weight="bold", font="Times New Roman", color=(128, 128, 128)
    )
    language_greetings = [
      GreetingDict(language="english", text="hello"),
      GreetingDict(language="german", text="hallo"),
      GreetingDict(language="french", text="bonjour"),
    ]
    wellcome_message = "{greeting}! Thank you for registration, {username}!"
    mailing_frequency = timedelta(days=5, hours=12)
    
    # And using these class variables in some methods...

All config values will be inserted and cast according to the type annotations once during the application or script start.

Different environments

Using this library it's easy to manage different environments and corresponding config files. It could be done like so:

import os
from conjector import properties


@properties(filename=os.getenv("CONFIG_FILENAME", "application.yml"))
class SomeEnvDependingService:
    env_depend_var: str

In this case, you can set CONFIG_FILENAME=application-dev.yml in env variables, and conjector will use that file.

About contributing

You will make conjector better if you open issues or create pull requests with improvements.