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