# Redis-Celery (Distributed Architecture)

This includes  
* Redis
* Flower

![sample case](media/messageImage_1712810451767.jpg)
![sample case](media/messageImage_1712810331954.jpg)

## Usage (docker-compose)
* start the system  
``` docker-compose up ```  
add ``` -d ``` run in background  
* down the system   
ctrl-c or  
``` docker-compose down ```  

## Celery
[Celery Documentation](https://docs.celeryq.dev/en/stable/index.html)  
[Flower Documentation](https://flower.readthedocs.io/en/latest/auth.html)
### install Celery
``` 
pip install -U "celery[redis]" 
```

### Starting the worker
```
celery -A proj worker 
```

### Options
```
Worker Options:
  -n, --hostname HOSTNAME         Set custom hostname (e.g., 'w1@%%h').  
                                  Expands: %%h (hostname), %%n (name) and %%d, (domain).  
  -D, --detach                    Start worker as a background process.  
  -S, --statedb PATH              Path to the state database. The extension  
                                  '.db' may be appended to the filename.  
  -l, --loglevel [DEBUG|INFO|WARNING|ERROR|CRITICAL|FATAL]  
                                  Logging level.  
  -O, --optimization [default|fair]  
                                  Apply optimization profile.  
  --prefetch-multiplier <prefetch multiplier>  
                                  Set custom prefetch multiplier value for  
                                  this worker instance.  
Pool Options:  
  -c, --concurrency <concurrency>  
                                  Number of child processes processing the  
                                  queue.  The default is the number of CPUs  
                                  available on your system.  
```  
celery worker --help can get more infomation.  

### woker in Windows  
add ``` --pool=solo ```  option   

### Calling the task
```shell
>>> from tasks import hello
>>> hello.delay()
```
If your celery app set rsult backend
```
>>> from tasks import hello  
>>> result = hello.delay()
```
The ready() method returns whether the task has finished processing or not:
```
>>> result.ready()
>>> False
```
You can wait for the result to complete, but this is rarely used since it turns the asynchronous call into a synchronous one:
```
>>> result.get(timeout=1)
>>> 'hello world'
```