Small boiler plate with tools for multithreading.
Project description
minibone
minbone is a small boiler plate with tools for multithreading and others.
- Config: To handle configuration setting
- Daemon: For multithreading tasks
- Logging: To setup a logger friendly with filerotation
- Among others (I will add more later)
It will be deployed to PyPi when a new release is created
Installation
pip install minibone
Config
Allows to handle configuration settings in memory and/or persists them into toml/yaml/json formats
from minibone.config import Config
# Create a new set of settings and persists them
cfg = Config(settings={"listen": "localhost", "port": 80}, filepath="config.toml")
cfg.add("debug", True)
cfg.to_toml()
# Load settings from a file. Defaults can be set. More information: help(Config.from_toml)
cfg2 = Config.from_toml("config.toml")
Usually config files are editted externaly then loaded as read only on your code, so in such case, you may want to subclass Config for easier usage
from minibone.config import Config
class MyConfig(Config):
def __init__(self):
defaults = {"main": {"listen": "localhost", "port": 80}}
settings = Config.from_toml(filepath="config.toml", defaults=defaults)
super().__init__(settings=settings)
def listen(self) -> str:
return self["main"]["listen"]
def port(self) -> int:
return self["main"]["port"]
if __name__ == "__main__":
cfg = MyConfig()
print(cfg.port())
# it will print the default port value if not port setting was defined in config.toml
Logging
It allows to setup a logger using UTC time that outputs to stderr or to a file. It is friendly to filerotation when setting output to a file
import logging
from minibone.logging import setup_log
if __name__ == "__main__":
# setup_log must be called only once in your code.
# So you have to choice if logging to stderr or to a file when calling it
setup_log(level="INFO")
logging.info('This is a log to the stderr')
# or call the next lines instead if you want to log into a file
# setup_log(file="sample.log", level="INFO")
# logging.info('yay!')
Daemon
It is just another python class to do jobs / tasks in the background using threads. It can be used in two modes: subclasing and callback
Usage as SubClass mode
- Subclass Daemon
- call super().init() in yours
- Overwrite on_process method with yours
- Add logic you want to run inside on_process
- Be sure your methods are safe-thread to avoid race condition
- self.lock is available for { lock.acquire => your_logic => lock.release }
- call start() method to keep running on_process in a new thread
- call stop() to finish the thread
Check sample_clock.py for a sample
Usage as callback mode
- Instance Daemon by passing a callable
- Add logic to your callable method
- Be sure your callable and methods are safe-thread to avoid race condition
- call start() method to keep running callable in a new thread
- call stop() to finish the thread
Check sample_clock_callback.py for a sample
Contribution
- Feel free to clone this repository, and send any pull requests.
- Add issues if something is not working as expected.
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