README

philiprehberger-progress-map

Parallel map with a built-in terminal progress bar.

Installation

pip install philiprehberger-progress-map

from philiprehberger_progress_map import pmap

def process(x):
    return x * 2

results = pmap(process, range(100))

Use multiprocessing instead of threading:

results = pmap(process, range(100), mp=True, workers=8)

Customize the progress display:

results = pmap(process, items, label="Processing", show_progress=True)

Parameter	Type	Default	Description
`func`	`Callable[[T], R]`	—	Function to apply to each item
`items`	`Iterable[T]`	—	Iterable of items to process
`workers`	`int`	`4`	Number of worker threads or processes
`mp`	`bool`	`False`	Use multiprocessing instead of threading
`label`	`str`	`""`	Optional label prefix for the progress bar
`show_progress`	`bool`	`True`	Whether to display the progress bar

Returns: list[R] — Results in the same order as the input items.

pip install -e .
python -m pytest tests/ -v

If you find this project useful:

Parallel map with a built-in terminal progress bar.

pip install philiprehberger-progress-map

from philiprehberger_progress_map import pmap

def process(x):
    return x * 2

results = pmap(process, range(100))

Use multiprocessing instead of threading:

results = pmap(process, range(100), mp=True, workers=8)

Customize the progress display:

results = pmap(process, items, label="Processing", show_progress=True)

Parameter	Type	Default	Description
`func`	`Callable[[T], R]`	—	Function to apply to each item
`items`	`Iterable[T]`	—	Iterable of items to process
`workers`	`int`	`4`	Number of worker threads or processes
`mp`	`bool`	`False`	Use multiprocessing instead of threading
`label`	`str`	`""`	Optional label prefix for the progress bar
`show_progress`	`bool`	`True`	Whether to display the progress bar

Returns: list[R] — Results in the same order as the input items.

pip install -e .
python -m pytest tests/ -v

If you find this project useful: