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Easy Python multiprocessing

Project description

# easy_multip

easy_multip is a small tool designed to quickly allow Python multiprocessing capabilities while greatly simplifying code for easier use.

# Current Features

- easy_multip.map(func, arg_group, leave_one_cpu_free=True)
- map() or list comprehension type functionality that is parallelized using multiprocessing and includes a progress bar
- Usage is similar to the below constructs:
```sh
list(map(func, arg_group))
or
[func(arg) for arg in arg_group]
```
- easy_multip.doloop(func, arg_group, leave_one_cpu_free=True)
- for loop equivalent that runs a function that returns None
- Useful in situations like file processing where each operation is expensive and totally independent
- Allocates jobs evenly among processors and provides a progress bar... of sorts
- Usage is similar to the below construct:
```sh
for arg in arg_group:
func(arg)
```
- easy_multip.decorators.use_multip(func, leave_one_cpu_free=True)
- Decorator providing capability of quickly adding multiprocessing to a function operating on a list
- ONLY for functions taking a list first arg that returns a list or None
- DO NOT USE `@decorator` syntax! Must use the following pattern:
```sh
def _func(list_arg, *args, **kwargs):
# stuff happens
return [] (or None)
func = use_multip(_func)
```

License
----
MIT

Project details


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